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Continuous Execution of High-Level Collaborative Tasks for Heterogeneous Robot Teams

Amy Fang, Tenny Yin, Jiawei Lin, Hadas Kress-Gazit

TL;DR

This work addresses coordinating a heterogeneous multi-robot team to satisfy collaborative tasks where actions have nonzero durations. It encodes tasks in $LTL^ψ$ with bindings and synthesizes team assignments and discrete behaviors whose continuous-time execution remains correct-by-construction, including synchronization for collaborative steps. The core methodology augments Büchi automata with intermediate transitions to enforce sequencing of non-instantaneous actions and iteratively updates per-robot product automata during a DFS-based teaming search. The approach is demonstrated on physical robots in warehouse-like scenarios, highlighting timing-aware correctness and the trade-offs between centralized and decentralized planning as action durations vary. Overall, it advances reliable, timing-consistent multi-robot collaboration under temporal and synchronization constraints in realistic settings.

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^ψ, 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.

Continuous Execution of High-Level Collaborative Tasks for Heterogeneous Robot Teams

TL;DR

This work addresses coordinating a heterogeneous multi-robot team to satisfy collaborative tasks where actions have nonzero durations. It encodes tasks in with bindings and synthesizes team assignments and discrete behaviors whose continuous-time execution remains correct-by-construction, including synchronization for collaborative steps. The core methodology augments Büchi automata with intermediate transitions to enforce sequencing of non-instantaneous actions and iteratively updates per-robot product automata during a DFS-based teaming search. The approach is demonstrated on physical robots in warehouse-like scenarios, highlighting timing-aware correctness and the trade-offs between centralized and decentralized planning as action durations vary. Overall, it advances reliable, timing-consistent multi-robot collaboration under temporal and synchronization constraints in realistic settings.

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^ψ, 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.

Paper Structure

This paper contains 23 sections, 7 equations, 8 figures, 4 algorithms.

Table of Contents

  1. Introduction
  2. Related Work
  3. Preliminaries
  4. Linear Temporal Logic
  5. Büchi Automata
  6. Definitions
  7. Actions
  8. Robot Model
  9. Task Grammar - LTL$^\psi$
  10. Problem Statement
  11. Approach
  12. Büchi Automaton for an LTL$^\psi$ Formula
  13. Constructing the Product Automaton
  14. Adding Intermediate Transitions to the Büchi Automaton
  15. Updating the Product Automaton
  16. ...and 8 more sections

Figures (8)

  • Figure 1: Partial model of robot $A_{blue}$ (see Sec. \ref{['sec:setup']}): (a) $\lambda_{\mathit{beep}}$ (b) $\lambda_{\mathit{motion}}$ (c) $A_{blue}$
  • Figure 2: Büchi automaton for Task 1
  • Figure 3: Environment and robot setup
  • Figure 4: Updated Büchi automaton for Case 1 ($e_1$ is a self-transition and $e_2$ is not). The blue represents the original transitions, the pink represents the added intermediate states and transitions
  • Figure 5: Initial setup on the physical system
  • ...and 3 more figures

Theorems & Definitions (9)

  • Remark 1
  • Remark 2
  • Remark 3
  • Definition 1: Binding Transition Function
  • Definition 2: Binding Set Function
  • Definition 3: Capability Function
  • Definition 4: Binding Assignment Function
  • Definition 5: Product Automaton
  • Definition 6: Intermediate Propositions Function