I am currently working as a senior software engineer at MathWorks in the Control Design Automation department for development of Simulink. Simulink is a block diagram environment used worldwide for design, simulation, code generation, test, and verification of various multi-domain dynamical systems.

I received the PhD degree in systems engineering from Boston University in 2014. During my PhD I was a member of the Hybrid and Networked Systems Lab (HyNeSs) and my research focused on formal control synthesis and path planning for autonomous vehicles. I received the B.S. degree in microelectronics engineering and the M.S. degree in electronics engineering from Sabanci University, Istanbul, Turkey, in 2007 and 2009, respectively. From 2008 to 2010, I was a Senior Design Engineer at Vestek R&D, Inc. in the RTL Group. For more information, please see my research, publications, and my curriculum vitae.

Mar 5, 2015
Simulink's new release R2015a is available. Check out the release highlights and the new Bus Smart Editing Cue.
Dec 5, 2014
NASA's Orion Exploration Flight Test-1 was completed successfully. Read the press release to learn how MathWorks products MATLAB, Simulink, and Stateflow contributed to this success.
July 19, 2014
MATLAB was in top 10 in IEEE Spectrum's The Top Programming Languages 2014 Ranking.
July 1, 2014
Our DARS 2012 paper was published as a book chapter in "Distributed Autonomous Robotic Systems: The 11th International Symposium" by Springer.
May 2, 2014
Our paper on receding horizon temporal logic control in dynamic environments will appear in IJRR.
Jan 30, 2014
Our paper on soft-landing control by control invariance and receding horizon control will appear at ACC 2014.
Jan 27, 2014
I started working as a senior software engineer at MathWorks.
Dec 18, 2013
I successfully defended my PhD dissertation titled "Optimal Temporal Logic Control of Autonomous Vehicles".
Dec 11, 2013
Our paper on incremental controller synthesis in probabilistic environments with temporal logic constraints will appear in IJRR.
Jun 5, 2013
I received an RSS 2013 student travel grant.
Apr 25, 2013
Our paper on receding horizon control in dynamic environments from temporal logic specifications will appear at RSS 2013.
Apr 12, 2013
I will be an intern at Mitsubishi Electric Research Laboratories (MERL) for three months.
Apr 4, 2014
Our work on wireless control networks with real-time constraints was published as a book chapter in "Industrial Wireless Sensor Networks: Applications, Protocols, and Standards" by CRC Press.
Apr 4, 2013
Our paper on optimality and robustness in multi-robot path planning with temporal logic constraints will appear in IJRR.
Jan 7, 2013
Our paper on temporal logic control for an autonomous quadrotor in a nondeterministic environment will appear at ICRA 2013.
Jan 7, 2013
Our paper on incremental synthesis of control policies for heterogeneous multi-agent systems with linear temporal logic specifications will appear at ICRA 2013.
Dec 6, 2012
Our paper on temporal logic robot control based on automata learning of environmental dynamics will appear in IJRR.
Sep 24, 2012
I was granted a DARS 2012 student travel award.
Sep 1, 2012
I received a CDC 2012 travel award.
Aug 22, 2012
Our paper on guaranteeing correctness through synchronization in multi-robot optimal path planning will appear at DARS 2012.
Jul 17, 2012
Our paper on incremental control synthesis in probabilistic environments with temporal logic constraints will appear at CDC 2012.
Jul 2, 2012
Our paper on incremental temporal logic synthesis of control policies for robots interacting with dynamic agents will appear at IROS 2012.
Jun 7, 2012
I received the first place prize in the SE photo contest for my photo of a closeup of a brainstorming session: arduino uno board and custom-designed xbee shield for arduino. See the winning photo!
May 8, 2012
I received an ICRA 2012 travel award.
Mar 23, 2012
I received a CISE Honorable Mention for my poster presentation at the 2012 BU Science and Engineering Day. Read the official announcement! The awards will be presented at the CISE Awards Ceremony. A short description of the award is as follows:
Entries were judged on scientific or engineering innovation, relevance, promise of future impact, societal implications, and the exhibitor's presentation.
Dec 31, 2011
Our paper on robust temporal logic planning will appear at ICRA 2012.
Nov 02, 2011
I was awarded a travel grant by the IROS 2011 Student Travel Awards Committee.
Oct 13, 2011
I was awarded a travel support grant by the Division of Systems Engineering.
Jun 24, 2011
Our paper on optimal multi-robot path planning with temporal logic constraints will appear at IROS 2011.

Journal Articles

  1. A. Ulusoy, C. Belta, "Receding Horizon Temporal Logic Control in Dynamic Environments," The International Journal of Robotics Research, to appear. [abstract, pdf, bibtex, video]
Abstract: We present a receding horizon method for controlling an autonomous vehicle that must satisfy a rich mission specification over service requests occurring at the regions of a partitioned environment. The overall mission specification consists of a temporal logic statement over a set of static, a priori known requests, a regular expression over a set of dynamic requests that can be sensed only locally, and a servicing priority order over these dynamic requests. Our approach is based on two main steps. First, we construct an abstraction for the motion of the vehicle in the environment by using input output linearization and assignment of vector fields to the regions in the partition. Second, a receding horizon controller computes local plans within the sensing range of the vehicle such that both local and global mission specifications are satisfied. We implement and evaluate our method through experiments and simulations consisting of a quadrotor performing a persistent surveillance task over a planar grid environment.
Full text of this paper is available at |IJRR|.
Digital object identifier of this paper is 10.1177/0278364914537008.
@article{ulusoy-ijrr2014b,
author={A. Ulusoy and C. Belta},
title={Receding Horizon Temporal Logic Control in Dynamic Environments},
journal={International Journal of Robotics Research},
volume={to appear},
number={to appear},
pages={to appear},
year={to appear},
}
  1. A. Ulusoy, T. Wongpiromsarn, C. Belta, "Incremental Controller Synthesis in Probabilistic Environments with Temporal Logic Constraints," The International Journal of Robotics Research, vol. 33, no. 8, pp. 1130–1144, 2014. [abstract, pdf, bibtex, video]
Abstract: In this paper, we consider automatic computation of optimal control strategies for a robot interacting with a set of independent uncontrollable agents in a graph-like environment. The mission specification is given as a syntactically co-safe Linear Temporal Logic formula over some properties that hold at the vertices of the environment. The robot is assumed to be a deterministic transition system, while the agents are probabilistic Markov models. The goal is to control the robot such that the probability of satisfying the mission specification is maximized. We propose a computationally efficient incremental algorithm based on the fact that temporal logic verification is computationally cheaper than synthesis. We present several case-studies where we compare our approach to the classical non-incremental approach in terms of computation time and memory usage.
Full text of this paper is available at |IJRR|.
Digital object identifier of this paper is 10.1177/0278364913519000.
@article{ulusoy-ijrr2014a,
author={A. Ulusoy and T. Wongpiromsarn and C. Belta},
title={Incremental Controller Synthesis in Probabilistic Environments with Temporal Logic Constraints},
journal={International Journal of Robotics Research},
volume={33},
number={8},
pages={1130--1144},
year={2014},
}
  1. A. Ulusoy, S. L. Smith, X. C. Ding, C. Belta, D. Rus, "Optimality and robustness in multi-robot path planning with temporal logic constraints," The International Journal of Robotics Research, vol. 32, no. 8, pp. 889–911, 2013. [abstract, pdf, bibtex, video]
Abstract: In this paper we present a method for automatic planning of optimal paths for a group of robots that satisfy a common high level mission specification. The motion of each robot is modeled as a weighted transition system, and the mission is given as a Linear Temporal Logic (LTL) formula over a set of propositions satisfied at the regions of the environment. In addition, an optimizing proposition must repeatedly be satisfied. The goal is to minimize a cost function that captures the maximum time between successive satisfactions of the optimizing proposition while guaranteeing that the formula is satisfied.
When the robots can follow a given trajectory exactly, our method computes a set of optimal satisfying paths that minimize the cost function and satisfy the LTL formula. However, if the traveling times of the robots are uncertain, then the robots may not be able to follow a given trajectory exactly, possibly violating the LTL formula during deployment. We handle such cases by leveraging the communication capabilities of the robots to guarantee correctness during deployment and provide bounds on the deviation from the optimal values. We implement and experimentally evaluate our method for various persistent surveillance tasks in a road network environment.
Full text of this paper is available at |IJRR|.
Digital object identifier of this paper is 10.1177/0278364913487931.
@article{ulusoy-ijrr2013,
author={A. Ulusoy and S. L. Smith and X. C. Ding and C. Belta and D. Rus},
title={Optimality and Robustness in Multi-Robot Path Planning with Temporal Logic Constraints},
journal={International Journal of Robotics Research},
volume={32},
number={8},
pages={889--911},
year={2013},
}
  1. Y. Chen, J. Tumova, A. Ulusoy, C. Belta, "Temporal Logic Robot Control based on Automata Learning of Environmental Dynamics," The International Journal of Robotics Research, vol. 32, no. 5, pp. 547–565, 2013. [abstract, pdf, bibtex, video]
Abstract: We develop a technique to automatically generate a control policy for a robot moving in an environment that includes elements with unknown, randomly changing behavior. The robot is required to achieve a surveillance mission, in which a certain request needs to be serviced repeatedly, while the expected time in between consecutive services is minimized and additional temporal logic constraints are satisfied. We define a fragment of Linear Temporal Logic (LTL) to describe such a mission and formulate the problem as a temporal logic game. Our approach is based on two main ideas. First, we extend results in automata learning to detect patterns of the unknown behavior of the elements in the environment. Second, we employ an automata-theoretic method to generate the control policy. We show that the obtained control policy converges to an optimal one when the partially unknown behavior patterns are fully learned. In addition, we illustrate the method in an experimental setup, in which an Unmanned Ground Vehicle (UGV), with the help of a cooperating Unmanned Aerial Vehicle (UAV), satisfies a temporal logic requirement in a partitioned environment whose regions are controlled by barriers with unknown behavior.
Full text of this paper is available at |IJRR|.
Digital object identifier of this paper is 10.1177/0278364912473168.
@inproceedings{chen-ijrr2013,
author={Y. Chen and J. Tumova and A. Ulusoy and C. Belta},
title={LTL Robot Motion Control based on Automata Learning of Environmental Dynamics},
journal={International Journal of Robotics Research},
volume={32},
number={5},
pages={547--565},
year={2013},
}
  1. Y. Sarikaya, I. C. Atalay, O. Gurbuz, O. Ercetin, A. Ulusoy, "Estimating the channel capacity of multi-hop IEEE 802.11 wireless networks," Ad Hoc Networks, vol. 10, no. 6, pp. 1058–1075, 2012. [abstract, pdf, bibtex, video]
Abstract: In IEEE 802.11 wireless networks, the residual capacity of the wireless links should be accurately estimated to realize advanced network services such as flow admission control or load balancing. In this paper, we propose an algorithm that estimates the packet delivery failure probability by collecting transmission statistics from nearby nodes, and by using a basic collision detection mechanism. This probability is then used in an analytical model to calculate the maximum allowable traffic needed to reach the saturation condition. We show by simulations that estimation error is within 0.5–5.0%, which is significantly lower than the best performance of prior estimation methods. We also demonstrate that the flow admission control is successfully achieved in a realistic wireless network scenario by the help of accurate link residual bandwidth estimation, where the unsatisfied traffic demand remain bounded at a negligibly low level. A routing algorithm that finds max–min residual bandwidth path between source and destination nodes is also implemented, and simulation results show that the network throughput achieved by this algorithm significantly exceeds that of other popular mesh routing protocols. Finally, we provide test results from the real implementation of our algorithm on 802.11 wireless equipment, which are consistent with the simulations.
Full text of this paper is available at ScienceDirect.
Digital object identifier of this paper is 10.1016/j.adhoc.2012.02.001.
@article{sarikaya-adhoc2012,
author={Y. Sarikaya and I. C. Atalay and O. Gurbuz and O. Ercetin and A. Ulusoy},
title={Estimating the Channel Capacity of Multi-Hop IEEE 802.11 Wireless Networks},
journal={Ad Hoc Networks},
volume={10},
number={6},
pages={1058--1075},
year={2012},
}
  1. A. Ulusoy, O. Gurbuz, A. Onat, "Wireless model based predictive networked control system over cooperative wireless network," IEEE Transactions on Industrial Informatics, vol. 7, no. 1, pp. 41–51, 2011. [abstract, pdf, bibtex, video]
Abstract: Owing to their distributed architecture, networked control systems (NCSs) are proven to be feasible in scenarios where a spatially distributed feedback control system is required. Traditionally, such NCSs operate over real-time wired networks. Recently, in order to achieve the utmost flexibility, scalability, ease of deployment, and maintainability, wireless networks such as IEEE 802.11 wireless local area networks (LANs) are being preferred over dedicated wired networks. However, conventional NCSs with event-triggered controllers and actuators cannot operate over such general purpose wireless networks since the stability of the system is compromised due to unbounded delays and unpredictable packet losses that are typical in the wireless medium. Approaching the wireless networked control problem from two perspectives, this work introduces a practical wireless NCS and an implementation of a cooperative medium access control protocol that work jointly to achieve decent control under severe impairments, such as unbounded delay, bursts of packet loss and ambient wireless traffic. The proposed system is evaluated on a dedicated test platform under numerous scenarios and significant performance gains are observed, making cooperative communications a strong candidate for improving the reliability of industrial wireless networks.
Full text of this paper is available at IEEE Xplore. You can also download my personal copy.
Digital object identifier of this paper is 10.1109/tii.2010.2089059.
@article{ulusoy-tii2012,
author={A. Ulusoy and O. Gurbuz and A. Onat},
title={Wireless Model Based Predictive Networked Control System over Cooperative Medium Access Control Protocol},
journal={IEEE Transactions on Industrial Informatics},
volume={7},
number={1},
pages={41--51},
year={2012},
}

Conference Articles

  1. S. Di Cairano, A. Ulusoy, S. Haghighat, "Soft-landing Control by Control Invariance and Receding Horizon Control," 2014 American Control Conference, pp. 784–789, Portland, OR, USA, 2014. [abstract, pdf, bibtex]
Abstract: We propose a methodology for soft landing control based on control invariant sets and receding horizon control. Soft landing control, which is of interest in several applications in automotive, aerospace, transportation systems, and factory automation, aims at achieving precise positioning of a moving object to a target position, while it ensures that the object maximum velocity decreases with the distance from the target. The resulting soft contact avoids damages and wear of parts. The constrained control techniques previously applied to soft-landing problems have limitations in terms of performance or complexity, and are not guaranteed to be robust to parameter uncertainty. In this paper, we formulate appropriate constraints and recast soft landing control as the generation of an admissible trajectory of the constrained system. Then, we compute a control invariant set for the system and design a receding horizon control law that forces the state to remain in such a control invariant set. Thus, the trajectories generated by the receding horizon controller are guaranteed to achieve soft landing, regardless of the controller cost function and horizon, and including the cases where the dynamics are uncertain. We demonstrate our approach by a case study in transportation systems.
Full text of this paper is available at IEEE Xplore.
Digital object identifier of this paper is 10.1109/|ACC|.2014.6858787.
@inproceedings{ulusoy-acc2104,
author={S. Di Cairano and A. Ulusoy and S. Haghighat},
title={Soft-landing Control by Control Invariance and Receding Horizon Control},
booktitle={American Control Conference},
pages={784--789},
year={2014},
}
  1. A. Ulusoy, M. Marrazzo, C. Belta, "Receding Horizon Control in Dynamic Environments from Temporal Logic Specifications," Robotics: Science and Systems 2013, Berlin, Germany, 2013. [abstract, pdf, bibtex, video]
Abstract: We present a control strategy for an autonomous vehicle that is required to satisfy a rich mission specification over service requests occurring at the regions of a partitioned environment. The overall mission specification consists of a temporal logic statement over a set of static, a priori known requests, and a servicing priority order over a set of dynamic requests that can be sensed locally. Our approach is based on two main steps. First, we construct an abstraction for the motion of the vehicle in the environment by using input output linearization and assignment of vector fields to the regions in the partition. Second, a receding horizon controller computes local plans within the sensing range of the vehicle such that both local and global mission specifications are satisfied. We implement and evaluate our method in an experimental setup consisting of a quadrotor performing a persistent surveillance task over a planar grid environment.
Full text of this paper is available online at RSS proceedings site. You can also download my personal copy.
Digital object identifier of this paper is not available yet.
@inproceedings{ulusoy-rss2013,
author={A. Ulusoy and M. Marrazzo and C. Belta},
title={Temporal Logic Control for an Autonomous Quadrotor in a Nondeterministic Environment},
booktitle={Proceedings of Robotics: Science and Systems},
pages={},
year={2013},
}
  1. A. Ulusoy, A. Onat, O. Gurbuz, "Wireless Model Based Predictive Networked Control System over IEEE 802.15.4," IEEE Intl. Conf. on Distributed Computing in Sensor Systems, pp. 382–387, Cambridge, MA, USA, 2013. [abstract, pdf, bibtex]
Abstract: Networked control systems offer significant advantages in terms of reliability, commissioning and maintenance, especially for complex systems. They must be able to withstand delays and data corruption caused by the underlying communication network. Existing results in networked control systems provide varying degrees of robustness. However, cost is also an important factor for real world implementations, which further restricts the bandwidth of the underlying network and complexity of the communication protocol. In this paper we introduce a networked control system method, WMBPNCS, that we have previously proposed, and implement a control system using IEEE 802.15.4 (ZigBee) as its communication protocol, in an attempt to overcome these problems. We find through simulations that performance of our implementation is acceptable even under large amounts of random network delay and data loss.
Full text of this paper is available online at IEEE Xplore.
Digital object identifier of this paper is 10.1109/DCOSS.2013.25
@inproceedings{ulusoy-dcoss2013,
author={A. Ulusoy and A. Onat and O. Gurbuz},
title={Wireless Model Based Predictive Networked Control System over IEEE 802.15.4},
booktitle={Distributed Computing in Sensor Systems (DCOSS), 2013 IEEE International Conference on},
pages={382--387},
year={2013},
}
  1. A. Ulusoy, M. Marrazzo, K. Oikonomopoulos, R. Hunter, C. Belta, "Temporal Logic Control for an Autonomous Quadrotor in a Nondeterministic Environment," IEEE Intl. Conf. on Robotics and Automation, pp. 331–336, Karlsruhe, Germany, 2013. [abstract, pdf, bibtex, video]
Abstract: We present an experimental setup for automatic deployment of a quadrotor in an environment with known topology and nondeterministically changing properties. The missions are specified as rich, temporal logic statements about the satisfaction of the properties. The main objective is to be able to synthesize, test, and evaluate control policies for complex aerial missions. Our testbed consists of quadrotors, a motion capture system that provides precise and continuous position information of the quadrotor, projectors that can emulate dynamically changing environments, physical obstacles, and computers that control the quadrotor, the motion capture system, and the projectors. Our computational approach is hierarchical. At the bottom level, we partition the environment and construct an abstraction in the form of a finite transition system such that the quadrotor can execute its transitions by using low level feedback controllers. At the top level, we draw inspiration from LTL model checking and use a value iteration algorithm to determine an optimal control policy that guarantees the satisfaction of the specification under nondeterministically changing properties. We illustrate the approach for the particular case of a surveillance mission in a city-like environment.
Full text of this paper is available online at IEEE Xplore. You can also download my personal copy.
Digital object identifier of this paper is 10.1109/|ICRA|.2013.6630596.
@inproceedings{ulusoy-icra2013,
author={A. Ulusoy and M. Marrazzo and K. Oikonomopoulos and R. Hunter and C. Belta},
title={Temporal Logic Control for an Autonomous Quadrotor in a Nondeterministic Environment},
booktitle={Robotics and Automation (ICRA), 2013 IEEE International Conference on},
pages={331--336},
year={2013},
}
  1. T. Wongpiromsarn, A. Ulusoy, C. Belta, E. Frazzoli, D. Rus, "Incremental Synthesis of Control Policies for Heterogeneous Multi-Agent Systems with Linear Temporal Logic Specifications," IEEE Intl. Conf. on Robotics and Automation, pp. 5011–5018, Karlsruhe, Germany, 2013. [abstract, pdf, bibtex]
Abstract: We consider automatic synthesis of control policies for non-independent, heterogeneous multi-agent systems with the objective of maximizing the probability of satisfying a given specification. The specification is expressed as a formula in linear temporal logic. The agents are modeled by Markov decision processes with a common set of actions. These actions, however, may or may not affect the behaviors of all the agents. To alleviate the well-known state explosion problem, an incremental approach is proposed where only a small subset of agents is incorporated in the synthesis procedure initially and more agents are successively added until the limitations on computational resources are reached. The proposed algorithm runs in an anytime fashion, where the probability of satisfying the specification increases as the algorithm progresses.
Full text of this paper is available online at IEEE Xplore. You can also download my personal copy.
Digital object identifier of this paper is 10.1109/|ICRA|.2013.6631293.
@inproceedings{wongpiromsarn-icra2013,
author={T. Wongpiromsarn and A. Ulusoy and C. Belta and E. Frazzoli and D. Rus},
title={Incremental Synthesis of Control Policies for Heterogeneous Multi-Agent Systems with Linear Temporal Logic Specifications},
booktitle={Robotics and Automation (ICRA), 2013 IEEE International Conference on},
pages={5011--5018},
year={2013},
}
  1. A. Ulusoy, T. Wongpiromsarn, C. Belta, "Incremental Control Synthesis in Probabilistic Environments with Temporal Logic Constraints," IEEE Conf. on Decision and Control, pp. 7658–7663, Maui, HI, USA, 2012. [abstract, pdf, bibtex]
Abstract: In this paper, we present a method for optimal control synthesis of a plant that interacts with a set of agents in a graph-like environment. The control specification is given as a temporal logic statement about some properties that hold at the vertices of the environment. The plant is assumed to be deterministic, while the agents are probabilistic Markov models. The goal is to control the plant such that the probability of satisfying a syntactically co-safe Linear Temporal Logic formula is maximized. We propose a computationally efficient incremental approach based on the fact that temporal logic verification is computationally cheaper than synthesis. We present a case-study where we compare our approach to the classical non-incremental approach in terms of computation time and memory usage.
Full text of this paper is available online at IEEE Xplore. You can also download my personal copy.
Digital object identifier of this paper is 10.1109/|CDC|.2012.6426346.
See the extended version of this paper.
@inproceedings{ulusoy-cdc2012,
author={A. Ulusoy and T. Wongpiromsarn and C. Belta},
title={Incremental Control Synthesis in Probabilistic Environments with Temporal Logic Constraints},
booktitle={Decision and Control (CDC), 2012 IEEE 51st Annual Conference on},
pages={7658--7663},
year={2012},
}
  1. A. Ulusoy, S. L. Smith, C. Belta, "Optimal Multi-Robot Path Planning with LTL Constraints: Guaranteeing Correctness Through Synchronization," Intl. Symp. on Distributed and Autonomous Robotic Systems, Baltimore, MD, USA. [abstract, pdf, bibtex, video]
Abstract: In this paper, we consider the automated planning of optimal paths for a robotic team satisfying a high level mission specification. Each robot in the team is modeled as a weighted transition system where the weights have associated deviation values that capture the non-determinism in the traveling times of the robot during its deployment. The mission is given as a Linear Temporal Logic (LTL) formula over a set of propositions satisfied at the regions of the environment. Additionally, we have an optimizing proposition capturing some particular task that must be repeatedly completed by the team. The goal is to minimize the maximum time between successive satisfying instances of the optimizing proposition while guaranteeing that the mission is satisfied even under non-deterministic traveling times. Our method relies on the communication capabilities of the robots to guarantee correctness and maintain performance during deployment. After computing a set of optimal satisfying paths for the members of the team, we also compute a set of synchronization sequences for each robot to ensure that the LTL formula is never violated during deployment. We implement and experimentally evaluate our method considering a persistent monitoring task in a road network environment.
This paper was published as a book chapter in "Distributed Autonomous Robotic Systems: The 11th International Symposium" by Springer. You can also download my personal copy.
See the extended version of this paper.
@inproceedings{ulusoy-dars2012,
author={A. Ulusoy and S. L. Smith and C. Belta},
title={Optimal Multi-Robot Path Planning with LTL Constraints: Guaranteeing Correctness Through Synchronization},
booktitle={Distributed and Autonomous Robotic Systems (DARS), International Symposium on},
pages={},
year={2012},
}
  1. T. Wongpiromsarn, A. Ulusoy, C. Belta, E. Frazzoli, D. Rus, "Incremental Temporal Logic Synthesis of Control Policies for Robots Interacting with Dynamic Agents," IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, pp. 229–236, Vila Moura, Portugal, 2012. [abstract, pdf, bibtex]
Abstract: We consider the synthesis of control policies from temporal logic specifications for robots that interact with multiple dynamic environment agents. Each environment agent is modeled by a Markov chain whereas the robot is modeled by a finite transition system (in the deterministic case) or Markov decision process (in the stochastic case). Existing results in probabilistic verification are adapted to solve the synthesis problem. To partially address the state explosion issue, we propose an incremental approach where only a small subset of environment agents is incorporated in the synthesis procedure initially and more agents are successively added until we hit the constraints on computational resources. Our algorithm runs in an anytime fashion where the probability that the robot satisfies its specification increases as the algorithm progresses.
Full text of this paper is available online at IEEE Xplore. You can also download my personal copy.
Digital object identifier of this paper is 10.1109/|IROS|.2012.6385575.
See the extended version of this paper.
@inproceedings{wongpiromsarn-iros2012,
author={T. Wongpiromsarn and A. Ulusoy and C. Belta and E. Frazzoli and D. Rus},
title={Incremental Temporal Logic Synthesis of Control Policies for Robots Interacting with Dynamic Agents},
booktitle={Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on},
pages={229--236},
year={2012},
}
  1. A. Ulusoy, S. L. Smith, X. C. Ding, C. Belta, "Robust Multi-Robot Optimal Path Planning with Temporal Logic Constraints," IEEE Intl. Conf. on Robotics and Automation, pp. 4693–4698, St. Paul, MN, USA, 2012. [abstract, pdf, bibtex, video]
Abstract: In this paper we present a method for automatically planning robust optimal paths for a group of robots that satisfy a common high level mission specification. Each robot's motion in the environment is modeled as a weighted transition system, and the mission is given as a Linear Temporal Logic (LTL) formula over a set of propositions satisfied by the regions of the environment. In addition, an optimizing proposition must repeatedly be satisfied. The goal is to minimize the maximum time between satisfying instances of the optimizing proposition while ensuring that the LTL formula is satisfied even with uncertainty in the robots' traveling times. We characterize a class of LTL formulas that are robust to robot timing errors, for which we generate optimal paths if no timing errors are present, and we present bounds on the deviation from the optimal values in the presence of errors. We implement and experimentally evaluate our method considering a persistent monitoring task in a road network environment.
Full text of this paper is available online at IEEE Xplore. You can also download my personal copy.
Digital object identifier of this paper is 10.1109/icra.2012.6224792.
See the extended version of this paper.
@inproceedings{ulusoy-icra2012,
author={A. Ulusoy and S. L. Smith and X. C. Ding and C. Belta},
title={Optimal Multi-Robot Path Planning with LTL Constraints: Guaranteeing Correctness Through Synchronization},
booktitle={Robotics and Automation (ICRA), 2012 IEEE International Conference on},
pages={4693--4698},
year={2012},
}
  1. A. Ulusoy, S. L. Smith, X. C. Ding, C. Belta, D. Rus, "Optimal Multi-Robot Path Planning with Temporal Logic Constraints," IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, pp. 3087–3092, San Francisco, CA, USA, 2011. [abstract, pdf, bibtex, video]
Abstract: In this paper we present a method for automatically planning optimal paths for a group of robots that satisfy a common high level mission specification. Each robot's motion in the environment is modeled as a weighted transition system. The mission is given as a Linear Temporal Logic formula. In addition, an optimizing proposition must repeatedly be satisfied. The goal is to minimize the maximum time between satisfying instances of the optimizing proposition. Our method is guaranteed to compute an optimal set of robot paths. We utilize a timed automaton representation in order to capture the relative position of the robots in the environment. We then obtain a bisimulation of this timed automaton as a finite transition system that captures the joint behavior of the robots and apply our earlier algorithm for the single robot case to optimize the group motion. We present a simulation of a persistent monitoring task in a road network environment.
Full text of this paper is available online IEEE Xplore. You can also download my personal copy.
Digital object identifier of this paper is 10.1109/iros.2011.6094884.
See the extended version of this paper.
@inproceedings{ulusoy-iros2011,
author={A. Ulusoy and S. L. Smith and X. C. Ding and C. Belta and D. Rus},
title={Optimal Multi-Robot Path Planning with Temporal Logic Constraints},
booktitle={Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on},
pages={3087--3092},
year={2011},
}
  1. A. Ulusoy, A. Onat, O. Gurbuz, "Wireless Model Based Predictive Networked Control System," IFAC Intl. Conf. on Fieldbusses and Networks in Industrial and Embedded Systems, pp. 40–47, Ansan, South Korea, 2009. [abstract, pdf, bibtex]
Abstract: Owing to their distributed architecture, networked control systems are proven to be feasible in scenarios where a spatially distributed control system is required. Traditionally, such networked control systems operate over real-time wired networks over which sensors, controllers and actuators interact with each other. Recently, in order to achieve the utmost flexibility, scalability, ease of deployment and maintainability, wireless networks such as IEEE 802.11 LANs are being preferred over dedicated wired networks. However, basic networked control systems cannot operate over general purpose wireless networks since the stability of the system is compromised due to unbounded delays and unpredictable packet losses that are typical in the wireless medium. This work proposes a novel wireless networked control system that can achieve decent control even under unbounded delay, bursts of packet loss and ambient wireless traffic. Ambient wireless traffic is handled with modified 802.11b medium access control parameters providing the proposed system with a greater medium access priority. Packet deadlines defined at each node of the system reduce unbounded packet delay to packet loss. Performance degradation due to packet loss is kept at a minimum using the predicted plant states and control signals. The proposed system is implemented and thoroughly evaluated on a dedicated test platform under numerous scenarios. Results of the experiments show that the proposed system can work under bursts of packet loss and ambient wireless traffic levels which are intolerable for basic networked control systems while not being hindered by restraining assumptions of existing methods.
Full text of this paper is available online at IFAC-PapersOnLine. You can also download my personal copy.
Digital object identifier of this paper is 10.3182/20090520-3-kr-3006.00007.
@inproceedings{ulusoy-fet2009,
author = {A. Ulusoy and A. Onat and O. Gurbuz},
title = {Wireless Model Based Predictive Networked Control System},
booktitle = {Fieldbusses and Networks in Industrial and Embedded Systems, 2009 IFAC Intl. Conf. on},
pages={40--71},
year={2009},
}
  1. E. Hatipoglu, A. Ulusoy, G. Kandemirli, "Effects of Oestrogen on Aquatic Ecosystems," Environment 2010 Intl. Symp. on Situation and Perspectives for the European Union, Porto, Portugal, 2003. [abstract, pdf, bibtex]
Abstract: Some aquatic pollutants mimic the effects of oestrogen. These substances effect both plants and invertebrates. Research showed that they cause the decrease in photosynthesis rate and heart rate of Daphina. In the food chain, these substances can be bioaccumulated and effect fish populations and those organisms that eat them including man. In this research, the aim was to determine the effect of ethynyloestardiol on the photosynthetic rate of Elodea and the heart rate of Daphina. Ethynyloestardiol was chosen as the oestrogenic substance because it could be easily obtained from birth control pills. Both Elodea and Daphina were chosen because they are common fresh water aquatic organisms. Elodea and Daphina were exposed to several different concentrations of oestradiol solutions. The photosynthetic rate was measured by comparing the amount of oxygen produced between control and experimental groups. The heart rate of Daphina was measured by counting heartbeat under the microscope and was compared to a control. The data was analyzed statistically and the results show that oestradiol decreases both the heart rate of Daphina and the rate of photosynthesis in Elodea.
Full text of this paper is available at Environment 2010 proceedings page. You can also download my personal copy.
@inproceedings{ulusoy-env2003,
author={E. Hatipoglu and A. Ulusoy and G. Kandemirli},
title={Effects of Oestrogen on Aquatic Ecosystems},
booktitle={Environment 2010 Intl. Symp. on Situation and Perspectives for the European Union},
pages={},
year={2003},
}

Book Chapters

  1. A. Ulusoy, S. L. Smith, C. Belta, "Optimal Multi-Robot Path Planning with LTL Constraints: Guaranteeing Correctness through Synchronization," in "Distributed Autonomous Robotic Systems: The 11th International Symposium", pp. 337–351, Springer, 2014. [bibtex, purchase]
@incollection{ulusoy-dars11,
author={A. Ulusoy and S. L. Smith and C. Belta},
title={Optimal Multi-Robot Path Planning with LTL Constraints: Guaranteeing Correctness through Synchronization},
editor={M. A. Hsieh and G. Chirikjian},
booktitle={Distributed Autonomous Robotic Systems: The 11th International Symposium},
pages={337--351},
series={Springer Tracts in Advanced Robotics},
publisher={Springer},
year={2014},
isbn={978-3642551451},
}
  1. A. Ulusoy, A. Onat, O. Gurbuz, "Wireless Control Networks with Real-Time Constraints," in "Industrial Wireless Sensor Networks: Applications, Protocols, Standards, and Products", pp. 207–230, CRC press, 2013. [bibtex, purchase]
@incollection{ulusoy-iwsn2013,
author={A. Ulusoy and A. Onat and O. Gurbuz},
title={Wireless Control Networks with Real-Time Constraints},
editor={V. C. Gungor and G. P. Hancke},
booktitle={Industrial Wireless Sensor Networks: Applications, Protocols, Standards, and Products},
pages={207--230},
series={Industrial Electronics},
publisher={CRC Press},
year={2013},
isbn={978-1466500518},
}

Books

  1. A. Ulusoy, O. Gurbuz, A. Onat, "Cooperative Wireless Model Based Predictive Networked Control Systems: Design, Implementation and Analysis," Lambert Academic Publishing, 2010. [bibtex, note, purchase]
@book{cwmbpncs-2010,
author={A. Ulusoy and O. Gurbuz and A. Onat},
title={Cooperative Wireless Model Based Predictive Networked Control Systems: Design, Implementation and Analysis},
year= {2010},
publisher= {Lambert Academic Publishing},
isbn={978-3843373999},
}
This book is based on my master's thesis.

Theses

  1. A. Ulusoy, "Optimal Temporal Logic Control of Autonomous Vehicles," PhD Dissertation, Boston University, Division of Systems Engineering, 2014. [abstract, pdf, bibtex]
Abstract: Temporal logics, such as Linear Temporal Logic (LTL) and Computation Tree Logic (CTL), are extensions of propositional logic that can capture temporal relations. Even though temporal logics have been used in model checking of finite systems for quite some time, they have gained popularity as a means for specifying complex mission requirements in path planning and control synthesis problems only recently. This dissertation proposes and evaluates methods and algorithms for optimal path planning and control synthesis for autonomous vehicles where a high-level mission specification expressed in LTL (or a fragment of LTL) must be satisfied. In summary, after obtaining a discrete representation of the overall system, ideas and tools from formal verification and graph theory are leveraged to synthesize provably correct and optimal control strategies.
The first part of this dissertation focuses on automatic planning of optimal paths for a group of robots that must satisfy a common high level mission specification. The effect of slight deviations in traveling times on the behavior of the team is analyzed and methods that are robust to bounded non-determinism in traveling times are proposed. The second part focuses on the case where a controllable agent is required to satisfy a high-level mission specification in the presence of other probabilistic agents that cannot be controlled. Efficient methods to synthesize control policies that maximize the probability of satisfaction of the mission specification are presented. The focus of the third part is the problem where an autonomous vehicle is required to satisfy a rich mission specification over service requests occurring at the regions of a partitioned environment. A receding horizon control strategy that makes use of the local information provided by the sensors on the vehicle in addition to the a priori information about the environment is presented. For all of the automatic planning and control synthesis problems that are considered, the proposed algorithms are implemented, evaluated, and validated through experiments and/or simulations.
Full text of my PhD dissertation is not available online yet.
@phdthesis{ulusoy-phdthesis,
title={Optimal Temporal Logic Control of Autonomous Vehicles},
author={A. Ulusoy},
school={Boston University},
year={2014},
}
  1. A. Ulusoy, "Design, Implementation and Analysis of Wireless Model Based Predictive Networked Control System over Cooperative Wireless Network," Master's Thesis, Sabanci University, Faculty of Engineering and Natural Sciences, 2009. [abstract, pdf, bibtex, video]
Abstract: Owing to their distributed architecture, networked control systems are proven to be feasible in scenarios where a spatially distributed control system is required. Traditionally, such networked control systems operate over real-time wired networks over which sensors, controllers and actuators interact with each other. Recently, in order to achieve the utmost flexibility, scalability, ease of deployment and maintainability, wireless networks such as IEEE 802.11 LANs are being preferred over dedicated wired networks. However, basic networked control systems cannot operate over such general purpose wireless networks since the stability of the system is compromised due to unbounded delays and unpredictable packet losses that are typical in the wireless medium.
Approaching the wireless networked control problem from two perspectives, this thesis proposes a novel wireless networked control system and a realistic cooperative medium access control protocol implementation that work jointly to achieve decent control even under unbounded delay, bursts of packet loss and ambient wireless traffic. The proposed system is implemented and thoroughly evaluated on a dedicated test platform under numerous scenarios and is shown to be operational under bursts of packet loss and ambient wireless traffic levels which are intolerable for basic networked control systems while not being hindered by restraining assumptions of existing methods.
Download the full text.
This work was also published as a book by Lambert Academic Publishing.
@mastersthesis{ulusoy-msthesis,
title={Design, Implementation and Analysis of Wireless Model Based Predictive Networked Control System over Cooperative Wireless Network},
author={A. Ulusoy},
school={Sabanci University},
year={2009},
}

Technical Reports and Extended Versions of Conference Articles

  1. A. Ulusoy, T. Wongpiromsarn, C. Belta, "Incremental Control Synthesis in Probabilistic Environments with Temporal Logic Constraints," arXiv, 2012. [pdf]
Full text of this paper is available online at arXiv. See the abridged (original) version of this paper.
  1. A. Ulusoy, S. L. Smith, C. Belta, "Optimal Multi-Robot Path Planning with LTL Constraints: Guaranteeing Correctness Through Synchronization," arXiv, 2012. [pdf]
Full text of this paper is available online at arXiv. See the abridged (original) version of this paper.
  1. T. Wongpiromsarn, A. Ulusoy, C. Belta, E. Frazzoli, D. Rus, "Incremental Temporal Logic Synthesis of Control Policies for Robots Interacting with Dynamic Agents," arXiv, 2012. [pdf]
Full text of this paper is available online at arXiv. See the abridged (original) version of this paper.
  1. A. Ulusoy, S. L. Smith, X. C. Ding, C. Belta, "Robust Multi-Robot Optimal Path Planning with Temporal Logic Constraints," arXiv, 2012. [pdf]
Full text of this paper is available online at arXiv. See the abridged (original) version of this paper.
  1. A. Ulusoy, S. L. Smith, X. C. Ding, C. Belta, D. Rus, "Optimal multi-robot path planning with temporal logic constraints," arXiv, 2011. [pdf]
Full text of this paper is available online at arXiv. See the abridged (original) version of this paper.

Poster Presentations

  1. "Incremental Controller Synthesis in Probabilistic Environments with Temporal Logic Constraints", RSS 2013 4th Workshop on Formal Methods for Robotics and Automation, Technische Universität München, Berlin, Germany.
  2. "Optimality and Robustness in Multi-Robot Path Planning", The 2012 Symposium on Emerging Topics in Control and Modeling: Networked Systems, University of Illinois at Urbana-Champaign.
  3. "Optimality and Robustness in Multi-Robot Path Planning", Boston University Science and Engineering Day 2012, (honorable mention).

LTL Optimal Multi-Agent Planner

LTL Optimal Multi-Agent Planner (LOMAP) is a python package for automatic planning of optimal paths for multi-agent systems. Learn more about LOMAP. I am planning to update this page frequently as the package matures.