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We propose a framework for the decentralized control of a team of agents that are assigned local tasks expressed as Linear Temporal Logic (LTL) formulas. Each local LTL task specification captures both the requirements on the respective…

Systems and Control · Computer Science 2014-05-09 Meng Guo , Jana Tumova , Dimos V. Dimarogonas

Collision-free navigation in cluttered environments with static and dynamic obstacles is essential for many multi-robot tasks. Dynamic obstacles may also be interactive, i.e., their behavior varies based on the behavior of other entities.…

Robotics · Computer Science 2024-05-21 Baskın Şenbaşlar , Gaurav S. Sukhatme

The majority of existing Linear Temporal Logic (LTL) planning methods rely on the construction of a discrete product automaton, that combines a discrete abstraction of robot mobility and a B$\ddot{\text{u}}$chi automaton that captures the…

Robotics · Computer Science 2021-03-24 Xusheng Luo , Yiannis Kantaros , Michael M. Zavlanos

In this paper, we present Stratified Topological Autonomy for Long-Range Coordination (STALC), a hierarchical planning approach for multi-robot coordination in real-world environments with significant inter-robot spatial and temporal…

Cooperative object transportation using multiple robots has been intensively studied in the control and robotics literature, but most approaches are either only applicable to omnidirectional robots or lack a complete navigation and…

Robotics · Computer Science 2023-07-24 Bingyi Xia , Hao Luan , Ziqi Zhao , Xuheng Gao , Peijia Xie , Anxing Xiao , Jiankun Wang , Max Q. -H. Meng

With the recent influx in demand for multi-robot systems throughout industry and academia, there is an increasing need for faster, robust, and generalizable path planning algorithms. Similarly, given the inherent connection between control…

Robotics · Computer Science 2024-01-23 Hussein Ali Jaafar , Cheng-Hao Kao , Sajad Saeedi

In this paper, we propose a model-free reinforcement learning method to synthesize control policies for motion planning problems with continuous states and actions. The robot is modelled as a labeled discrete-time Markov decision process…

Artificial Intelligence · Computer Science 2020-10-01 Chuanzheng Wang , Yinan Li , Stephen L. Smith , Jun Liu

Stable dynamical systems are a flexible tool to plan robotic motions in real-time. In the robotic literature, dynamical system motions are typically planned without considering possible limitations in the robot's workspace. This work…

Robotics · Computer Science 2020-03-26 Matteo Saveriano , Dongheui Lee

In this paper, we provide a framework integrating distributed multi-robot systems and temporal epistemic logic. We show that continuous-discrete hybrid systems are compatible with logical models of knowledge already used in distributed…

Logic in Computer Science · Computer Science 2025-09-01 Giorgio Cignarale , Stephan Felber , Eric Goubault , Bernardo Hummes Flores , Hugo Rincon Galeana

Linear temporal logic (LTL) is a compelling framework for specifying complex, structured tasks for reinforcement learning (RL) agents. Recent work has shown that interpreting LTL instructions as finite automata, which can be seen as…

Artificial Intelligence · Computer Science 2025-12-03 Mattia Giuri , Mathias Jackermeier , Alessandro Abate

Given a heterogeneous group of robots executing a complex task represented in Linear Temporal Logic, and a new set of tasks for the group, we define the task update problem and propose a framework for automatically updating individual robot…

Robotics · Computer Science 2022-04-19 Amy Fang , Hadas Kress-Gazit

The problem of planning for a robot that operates in environments containing a large number of objects, taking actions to move itself through the world as well as to change the state of the objects, is known as task and motion planning…

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

In this paper, we propose a novel methodology for path planning and scheduling for multi-robot navigation that is based on optimal transport theory and model predictive control. We consider a setup where $N$ robots are tasked to navigate to…

Robotics · Computer Science 2025-09-01 Usman A. Khan , Mouhacine Benosman , Wenliang Liu , Federico Pecora , Joseph W. Durham

Safe motion planning for robotic systems in dynamic environments is nontrivial in the presence of uncertain obstacles, where estimation of obstacle uncertainties is crucial in predicting future motions of dynamic obstacles. The worst-case…

Robotics · Computer Science 2025-01-22 Jian Zhou , Yulong Gao , Ola Johansson , Björn Olofsson , Erik Frisk

Multi-robot motion planning (MRMP) is the problem of finding collision-free paths for a set of robots in a continuous state space. The difficulty of MRMP increases with the number of robots and is exacerbated in environments with narrow…

Robotics · Computer Science 2023-11-17 Courtney McBeth , James Motes , Diane Uwacu , Marco Morales , Nancy M. Amato

Most current methods for learning from demonstrations assume that those demonstrations alone are sufficient to learn the underlying task. This is often untrue, especially if extra safety specifications exist which were not present in the…

Machine Learning · Computer Science 2020-05-26 Craig Innes , Subramanian Ramamoorthy

Floating-base multi-link robots can change their shape during flight, making them well-suited for applications in confined environments such as autonomous inspection and search and rescue. However, trajectory planning for such systems…

Robotics · Computer Science 2026-04-07 Yicheng Chen , Jinjie Li , Haokun Liu , Zicheng Luo , Kotaro Kaneko , Moju Zhao

Autonomous multi-robot optical inspection systems are increasingly applied for obtaining inline measurements in process monitoring and quality control. Numerous methods for path planning and robotic coordination have been developed for…

Robotics · Computer Science 2021-06-16 Yinhua Liu , Wenzheng Zhao , Tim Lutz , Xiaowei Yue

This study proposes a novel planning framework based on a model predictive control formulation that incorporates signal temporal logic (STL) specifications for task completion guarantees and robustness quantification. This marks the…

Robotics · Computer Science 2023-09-26 Zhaoyuan Gu , Rongming Guo , William Yates , Yipu Chen , Ye Zhao
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