Control of cooperative manipulator-endowed systems under high-level tasks and uncertain dynamics. (2022)

• Record Type: Journal Article
• Authors: Verginis, Christos K.; Dimarogonas, Dimos V.
• Is Part Of: Annual reviews in control. Volume 54(2022)
• Page Start: 219
• Page End: 240
• Publication Date: 2022
• Subjects: Multi-agent systems -- Multi-agent navigation -- Cooperative manipulation -- Uncertain dynamics -- Temporal-logics; Automatic control -- Periodicals; Periodicals; 629.805
• DOI: 10.1016/j.arcontrol.2022.09.004
• Languages: English
• ISSNs: 1367-5788

Abstract

Abstract: This paper considers the problem of distributed motion- and task-planning of multi-agent and multi-agent-object systems under temporal-logic-based tasks and uncertain dynamics. We focus on manipulator-endowed robotic agents that can interact with their surroundings. We present first continuous control algorithms for multi-agent navigation and cooperative object manipulation that exhibit the following properties. First, they are distributed in the sense that each agent calculates its own control signal from local interaction with the other agents and the environment. Second, they guarantee safety properties in terms of inter-agent collision avoidance and obstacle avoidance. Third, they adapt on-the-fly to dynamic uncertainties and are robust to exogenous disturbances. The aforementioned algorithms allow the abstraction of the underlying system to a finite-state representation. Inspired by formal-verification techniques, we use such a representation to derive plans for the agents that satisfy the given temporal-logic tasks. Various simulation results and hardware experiments verify the efficiency of the proposed algorithms.