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This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solution trajectory based on prediction and correction…

Information Theory · Computer Science 2017-09-18 Andrea Simonetto , Aryan Mokhtari , Alec Koppel , Geert Leus , Alejandro Ribeiro

Behavior Trees (BTs) provide designers an intuitive graphical interface to construct long-horizon plans for autonomous systems. To ensure their correctness and safety, rigorous formal models and verification techniques are essential.…

Robotics · Computer Science 2026-04-15 Ryan Matheu , John S. Baras , Calin Belta

We present the Temporal Logic Synthesis Format (TLSF), a high-level format to describe synthesis problems via Linear Temporal Logic (LTL). The format builds upon standard LTL, but additionally allows to use high-level constructs, such as…

Logic in Computer Science · Computer Science 2016-11-24 Swen Jacobs , Felix Klein , Sebastian Schirmer

This paper considers the problem of controller synthesis of signal temporal logic (STL) specifications for large-scale multi-agent systems, where the agents are dynamically coupled and subject to collaborative tasks. A compositional…

Systems and Control · Electrical Eng. & Systems 2025-03-18 Siyuan Liu , Adnane Saoud , Dimos V. Dimarogonas

This paper proposes a finitely terminating algorithm to solve reach-and-stay control problems for nonlinear systems. The algorithm is guaranteed to return a control strategy if the specification is robustly realizable. Such a feature is…

Optimization and Control · Mathematics 2020-04-17 Yinan Li , Jun Liu

The idea of automatic synthesis of reactive programs starting from temporal logic (LTL) specifications is quite old, but was commonly thought to be infeasible due to the known double exponential complexity of the problem. However, new ideas…

Logic in Computer Science · Computer Science 2011-02-22 Andreas Morgenstern , Klaus Schneider

Signal Temporal Logic (STL) offers verifiable task specifications and is crucial for safety-critical control. Yet STL planning remains challenging: exact optimization-based methods are often too slow, and learning-based methods struggle to…

Artificial Intelligence · Computer Science 2026-05-05 Bowen Ye , Ancheng Hou , Junyue Huang , Ruijia Liu , Xiang Yin

In this paper, we present a provably correct controller synthesis approach for switched stochastic control systems with metric temporal logic (MTL) specifications with provable probabilistic guarantees. We first present the stochastic…

Systems and Control · Electrical Eng. & Systems 2021-03-29 Zhe Xu , Yichen Zhang

We consider multi-robot systems under recurring tasks formalized as linear temporal logic (LTL) specifications. To solve the planning problem efficiently, we propose a bottom-up approach combining offline plan synthesis with online…

We present a method for synthesizing controllers to steer trajectories from an initial set to a target set on a finite time horizon. The proposed control synthesis problem is decomposed into two steps. The first step under-approximates the…

Systems and Control · Computer Science 2018-10-02 He Yin , Andrew Packard , Murat Arcak , Pete Seiler

We develop an assume-guarantee framework for control of large scale linear (time-varying) systems from finite-time reach and avoid or infinite-time invariance specifications. The contracts describe the admissible set of states and controls…

Systems and Control · Electrical Eng. & Systems 2020-02-18 Kasra Ghasemi , Sadra Sadraddini , Calin Belta

We study the problem of synthesizing a controller to satisfy a complex task in the presence of sensor faults and attacks. We model the task using Gaussian distribution temporal logic (GDTL), and propose a solution approach that does not…

Systems and Control · Electrical Eng. & Systems 2022-08-23 Luyao Niu , Zhouchi Li , Andrew Clark

Path planning for a robot is one of the major problems in the area of robotics. When a robot is given a task in the form of a Linear Temporal Logic (LTL) specification such that the task needs to be carried out repetitively, we want the…

Robotics · Computer Science 2021-03-05 Priya Purohit , Indranil Saha

This work develops a zero-shot mechanism, Comp-LTL, for an agent to satisfy a Linear Temporal Logic (LTL) specification given existing task primitives trained via reinforcement learning (RL). Autonomous robots often need to satisfy spatial…

Robotics · Computer Science 2024-12-17 Taylor Bergeron , Zachary Serlin , Kevin Leahy

This paper studies the controller synthesis problem for Linear Temporal Logic (LTL) specifications using (constrained) zonotope techniques. First, we implement (constrained) zonotope techniques to partition the state space and further to…

Systems and Control · Electrical Eng. & Systems 2021-11-16 Wei Ren , Julien Calbert , Raphael Jungers

Learning to control an unknown dynamical system with respect to high-level temporal specifications is an important problem in control theory. We present the first regret-free online algorithm for learning a controller for linear temporal…

Artificial Intelligence · Computer Science 2025-06-09 Rupak Majumdar , Mahmoud Salamati , Sadegh Soudjani

Efficient coordination and planning is essential for large-scale multi-agent systems that collaborate in a shared dynamic environment. Heuristic search methods or learning-based approaches often lack the guarantee on correctness and…

Robotics · Computer Science 2024-04-10 Zesen Liu , Meng Guo , Weimin Bao , Zhongkui Li

Temporal logic has been widely used to express complex task specifications for cyber-physical systems (CPSs). One way to synthesize a controller for CPS under temporal logic constraints is to first abstract the CPS as a discrete transition…

Systems and Control · Electrical Eng. & Systems 2021-09-28 Luyao Niu , Andrew Clark

In this work, we focus on decomposing large multi-agent path planning problems with global temporal logic goals (common to all agents) into smaller sub-problems that can be solved and executed independently. Crucially, the sub-problems'…

Artificial Intelligence · Computer Science 2022-03-17 Kevin Leahy , Austin Jones , Cristian-Ioan Vasile

Real-world environments are inherently uncertain, and to operate safely in these environments robots must be able to plan around this uncertainty. In the context of motion planning, we desire systems that can maintain an acceptable level of…

Robotics · Computer Science 2020-03-18 Charles Dawson , Ashkan Jasour , Andreas Hofmann , Brian Williams