Work

MAPS 2 : Multi-robot autonomous motion planning under signal temporal logic specifications

Year: 2025

Type: article

Abstract: This article presents MAPS 2 : a distributed algorithm that allows multi-robot systems to deliver coupled tasks expressed as Signal Temporal Logic (STL) constraints. Classical control theoretical tools addressing STL constraints either adopt a limited fragment of the STL formula or require approximations of min/max operators. Meanwhile, works maximising robustness through optimisation-based methods often suffer from local minima, thus relaxing any completeness arguments due to the NP-hard nature of the problem. Endowed with probabilistic guarantees, MAPS 2 provides an autonomous algorithm that iteratively improves the robots’ trajectories. The algorithm selectively imposes spatial constraints by taking advantage of the temporal properties of the STL. The algorithm is distributed in the sense that each robot calculates its trajectory by communicating only with its immediate neighbours as defined via a communication graph. We illustrate the efficiency of MAPS 2 by conducting extensive simulation and experimental studies, verifying the generation of STL satisfying trajectories.

Source: The International Journal of Robotics Research

DOI: 10.1177/02783649251393343

Authors: Mayank Sewlia, Christos K. Verginis, Dimos V. Dimarogonas

Institutions: KTH Royal Institute of Technology, Uppsala University

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,400

Funder: Vetenskapsrådet