Higher Order Reasoning for Collaborative Communicationless Mobile Robot Operations
Jonathan Reasoner, Nicola Bezzo
AI summary
Problem
Multi-robot coordination typically relies on constant communication, which fails in denied, jammed, or range-limited environments. This paper addresses how to effectively coordinate collaborative operations without explicit information exchange.
Approach
Robots propagate belief and empathy particles using Dynamic Epistemic Logic to model teammates' knowledge and predict future actions. This higher-order reasoning drives a behavior tree and MPPI controller to select adaptive, optimal trajectories under partial observability.
Key results
- A long-horizon estimation-planning-coordination framework coupling epistemic logic with belief-informed exploration
- Consistent reduction in task completion time compared to first-order baselines in simulations and experiments
- Robust implicit coordination and trajectory adaptation under partial observability and communication constraints
- Validation of the approach through both simulation and physical multi-robot experiments
Why it matters
Enables reliable multi-robot collaboration in communication-denied environments like disaster response or military operations where traditional coordination fails.
Abstract
In communicationless environments, multi-robot systems must operate without the constant information ex- change that many coordination strategies typically assume. This paper presents a novel dynamic epistemic planning framework that enables implicit coordination and long horizon planning through higher-order reasoning among robots. With our ap- proach, robots form and propagate higher-order belief particles, update world beliefs using Bayesian inference, and select actions via a behavior tree that anticipates teammates’ likely decisions. A temporally aware Model Predictive Path Integral (MPPI) controller integrates this reasoning into low-level execution, allowing robots to plan intercepts and adapt trajectories under partial observability. The proposed framework is evaluated in both simulations and physical experiments, where it consistently reduces task completion time compared to a first-order baseline, demonstrating that epistemic logic can serve as a robust foun- dation for resilient coordination in communication-restricted domains.