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Article
Robotics
Karen Leung et al.
Summary: This paper presents a technique called STLCG that computes the quantitative semantics of Signal Temporal Logic (STL) formulas using computation graphs. STLCG provides a platform for integrating logical specifications into robotics problems that benefit from gradient-based solutions. It translates STL robustness formulas into computation graphs and leverages off-the-shelf automatic differentiation tools to efficiently backpropagate through the formulas. Through examples, it is shown that STLCG is versatile, computationally efficient, and capable of incorporating human-domain knowledge into the problem formulation.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2023)
Article
Robotics
Wataru Hashimoto et al.
Summary: This letter presents a method for learning an RNN controller that maximizes the robustness of STL specifications. By introducing the concept of STL2vec, the controller can be efficiently constructed and validated through examples of path planning problem.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Dawei Sun et al.
Summary: This article addresses the challenging problem of multi-agent cooperative motion planning using signal temporal logic (STL) for complex tasks. A method based on timed waypoints is proposed and evaluated on various benchmarks, demonstrating its superiority over existing abstraction-based and model predictive control (MPC)-based motion planning methods for multi-agent planning with complex specifications and long planning horizons.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Automation & Control Systems
Yulong Gao et al.
Summary: The study proposes algorithms for model checking and control synthesis for discrete-time uncertain systems under linear temporal logic specifications. By constructing temporal logic trees, the algorithms provide underapproximations and overapproximations of LTL formulas. A controlled TLT can be constructed for controlled transition systems, allowing for online control synthesis and generation of feasible control inputs at each time step. The algorithms demonstrate generality and online scalability in both finite and infinite systems.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Lars Lindemann et al.
Summary: In this paper, we propose reactive risk signal interval temporal logic (ReRiSITL) for formulating complex spatiotemporal specifications and provide an algorithm to check its satisfiability. We also propose a reactive planning and control framework for dynamical control systems under ReRiSITL specifications.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Proceedings Paper
Automation & Control Systems
Qi Heng Ho et al.
Summary: This paper presents an algorithmic framework for control synthesis for continuous dynamical systems with signal temporal logic (STL) specifications. The authors propose a novel algorithm to obtain a time-partitioned finite automaton from an STL specification, and introduce a multi-layered framework that utilizes this automaton to guide a sampling-based search tree in both spatial and temporal dimensions. The approach is able to synthesize a controller for nonlinear dynamics and polynomial predicate functions, and the authors prove the correctness and probabilistic completeness of the algorithm. The efficacy and efficiency of the framework are demonstrated through several case studies, showing a significant speedup compared to the state of the art.
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Frank J. Jiang et al.
Summary: This paper presents a hardware and software testbed, named SVEA, designed for evaluating V2X usecases. The SVEA testbed consists of a communication software stack and a 1/10th-scale automated vehicle platform, enabling cost-effective and time-efficient experimentation with V2X use-cases. The paper also details three specific use-cases implemented on the SVEA testbed and discusses the current usage of the platform and future development plans.
2022 IEEE 25TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)
(2022)
Proceedings Paper
Automation & Control Systems
Guy Scher et al.
Summary: We develop a method for synthesizing control policies for stochastic, linear, time-varying systems that must perform tasks specified in signal temporal logic. The method efficiently computes the probability of system satisfaction and obtains sample-efficient gradients to optimize controllers that maximize the chances of satisfying the specification. The approach is demonstrated through examples of a mobile robot and a mobile manipulator in simulation.
2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2022)
Proceedings Paper
Computer Science, Software Engineering
Nathaniel Hamilton et al.
Summary: Reinforcement Learning relies on designing reward functions to capture intended behavior. Traditional approaches struggle to represent temporal behavior and require manual effort to create reward functions. To address this, we propose an automatic method to convert specifications into reward functions and demonstrate its effectiveness in training RL agents.
SOFTWARE ENGINEERING AND FORMAL METHODS, SEFM 2022
(2022)
Article
Automation & Control Systems
Vincent Kurtz et al.
Summary: Signal Temporal Logic (STL) provides a convenient way of encoding complex control objectives for robotic and cyber-physical systems. The state-of-the-art in trajectory synthesis for STL is based on Mixed-Integer Convex Programming (MICP). In this letter, we propose a more efficient MICP encoding for STL, which can encode disjunction using a logarithmic number of binary variables and encode conjunction without binary variables. Simulation examples demonstrate the superior performance of our proposed approach for long and complex specifications. Open-source software is available: https://stlpy.readthedocs.io.
IEEE CONTROL SYSTEMS LETTERS
(2022)
Article
Automation & Control Systems
Wenliang Liu et al.
Summary: This paper proposes a framework based on Recurrent Neural Networks (RNNs) to determine an optimal control strategy for a discrete-time system that satisfies Signal Temporal Logic (STL) formulae.
IEEE CONTROL SYSTEMS LETTERS
(2022)
Article
Robotics
Ali Tevfik Buyukkocak et al.
Summary: This study addresses the coordination of trajectories for heterogeneous multi-agent systems using global STL constraints and integral predicates to generate optimal agent movement while minimizing movement. The proposed method's performance is demonstrated through simulations and experiments with drones.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Proceedings Paper
Automation & Control Systems
Somil Bansal et al.
Summary: Hamilton-Jacobi (HJ) reachability analysis is an important formal verification method for performance and safety properties of dynamical control systems. DeepReach is a neural PDE solver that leverages sinusoidal networks to handle high-dimensional reachability problems, achieving comparable results to state-of-the-art methods and providing a safety controller for the system, without requiring explicit supervision for the PDE solution.
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
(2021)
Article
Automation & Control Systems
Yann Gilpin et al.
Summary: Signal Temporal Logic (STL) has gained popularity in formal specification for symbolic control due to its expressive nature close to natural language. Recent research has focused on using smooth approximations of robustness to enable faster methods for finding local maxima, albeit potentially sacrificing accuracy and/or completeness. A novel robustness approximation has been proposed, which is smooth, sound, and asymptotically complete, offering an explicit tradeoff between conservativeness and completeness.
IEEE CONTROL SYSTEMS LETTERS
(2021)
Proceedings Paper
Automation & Control Systems
Jesper Karlsson et al.
Proceedings Paper
Automation & Control Systems
Guang Yang et al.
2020 AMERICAN CONTROL CONFERENCE (ACC)
(2020)
Article
Automation & Control Systems
Yiannis Kantaros et al.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2019)
Article
Automation & Control Systems
Lars Lindemann et al.
Article
Automation & Control Systems
Samira S. Farahani et al.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2019)
Article
Robotics
Fernando S. Barbosa et al.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2019)
Article
Automation & Control Systems
Lars Lindemann et al.
IEEE CONTROL SYSTEMS LETTERS
(2019)
Article
Automation & Control Systems
Mo Chen et al.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2018)
Proceedings Paper
Automation & Control Systems
Hendrik Roehm et al.
AUTOMATED TECHNOLOGY FOR VERIFICATION AND ANALYSIS, ATVA 2016
(2016)
Proceedings Paper
Engineering, Electrical & Electronic
Eric M. Wolff et al.
ROBOTICS RESEARCH, ISRR
(2016)
Article
Computer Science, Theory & Methods
Georgios E. Fainekos et al.
THEORETICAL COMPUTER SCIENCE
(2009)
Article
Automation & Control Systems
Calin Belta et al.
IEEE ROBOTICS & AUTOMATION MAGAZINE
(2007)
