Continuous Execution of High-Level Collaborative Tasks for Heterogeneous Robot Teams
Amy Fang, Tenny Yin, Jiawei Lin, Hadas Kress-Gazit

TL;DR
This paper introduces a control synthesis framework for heterogeneous multi-robot systems to execute collaborative tasks continuously, using logic encoding and automatic synthesis to ensure correctness and synchronization.
Contribution
It presents a novel synthesis approach for continuous, correct-by-construction task execution in heterogeneous robot teams using LTL^ logic.
Findings
Successful implementation on a physical multi-robot system
Automatic generation of teaming assignments and behaviors
Ensured synchronization for collaborative tasks
Abstract
We propose a control synthesis framework for a heterogeneous multi-robot system to satisfy collaborative tasks, where actions may take varying duration of time to complete. We encode tasks using the discrete logic LTL^\psi, which uses the concept of bindings to interleave robot actions and express information about relationship between specific task requirements and robot assignments. We present a synthesis approach to automatically generate a teaming assignment and corresponding discrete behavior that is correct-by-construction for continuous execution, while also implementing synchronization policies to ensure collaborative portions of the task are satisfied. We demonstrate our approach on a physical multi-robot system.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsModular Robots and Swarm Intelligence · Distributed systems and fault tolerance · Collaboration in agile enterprises
