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Multi-Agent Control Synthesis from Global Temporal Logic Tasks with Synchronous Satisfaction Requirements

Tiange Yang, Yuanyuan Zou, Jinfeng Liu, Shaoyuan Li, Xiaohu Zhao

TL;DR

This paper addresses the multi-agent control problem under global temporal logic tasks, considering agents with heterogeneous capabilities, and proposes a mixed-integer linear programming (MILP) encoding method to realize task-satisfied motion planning with high synchronicity and minimum control efforts.

Abstract

This paper addresses the multi-agent control problem under global temporal logic tasks, considering agents with heterogeneous capabilities. These global tasks involve not only absolute and relative temporal and spatial constraints, but also group behaviors, including task completion times, agent capabilities, and task interdependencies such as the need for synchronous execution. The global tasks are formally formulated into global signal temporal logic (STL) formulae, and a synchronous robustness metric is designed to evaluate the synchronization quality with real values. A mixed-integer linear programming (MILP) encoding method is further proposed to realize task-satisfied motion planning with high synchronicity and minimum control efforts. The encoding method uses a logarithmic number of binary variables to fully capture synchronous robustness, leading to only linear computational complexity. Simulations are conducted to demonstrate the efficiency of the proposed control strategy.

Multi-Agent Control Synthesis from Global Temporal Logic Tasks with Synchronous Satisfaction Requirements

TL;DR

This paper addresses the multi-agent control problem under global temporal logic tasks, considering agents with heterogeneous capabilities, and proposes a mixed-integer linear programming (MILP) encoding method to realize task-satisfied motion planning with high synchronicity and minimum control efforts.

Abstract

This paper addresses the multi-agent control problem under global temporal logic tasks, considering agents with heterogeneous capabilities. These global tasks involve not only absolute and relative temporal and spatial constraints, but also group behaviors, including task completion times, agent capabilities, and task interdependencies such as the need for synchronous execution. The global tasks are formally formulated into global signal temporal logic (STL) formulae, and a synchronous robustness metric is designed to evaluate the synchronization quality with real values. A mixed-integer linear programming (MILP) encoding method is further proposed to realize task-satisfied motion planning with high synchronicity and minimum control efforts. The encoding method uses a logarithmic number of binary variables to fully capture synchronous robustness, leading to only linear computational complexity. Simulations are conducted to demonstrate the efficiency of the proposed control strategy.
Paper Structure (12 sections, 23 equations, 2 figures, 2 tables)

This paper contains 12 sections, 23 equations, 2 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Preliminaries
  3. Signal temporal logic
  4. System Model
  5. Global tasks syntax and semantics
  6. Syntax and qualitative semantics
  7. Synchronous robust semantics
  8. Control Synthesis
  9. Simulation
  10. Conclusion
  11. Acknowledgments
  12. Conflict of interest

Figures (2)

  • Figure 1: A farmland health monitoring scenario. The initial position of each agent is shown in the upper left corner. Blue circles, orange pentagons, and purple squares represent agents equipped with UV, IR, and Vis sensors, respectively.
  • Figure 2: Agent trajectories under the proposed motion planning algorithm

Theorems & Definitions (3)

  • Example 1
  • Remark 1
  • Remark 2