TDMA Based Communications Control Co-Design for Cooperative Carrying: Delay Calibration and Sampling-Rate Optimization

2026-08-10

AI Summary

This study addresses the challenge of simultaneously achieving communication efficiency, control stability, and fair wireless resource allocation in multi-robot cooperative transport. To this end, it proposes a coordination strategy integrating dynamic sampling rate adaptation with a leader rotation mechanism. Leveraging a physics-based simulation environment built on MuJoCo and incorporating TDMA scheduling, MAC-layer characteristics, and realistic channel effects—including jitter, queuing delays, and packet loss—the work presents the first joint analysis of how dynamic sampling, leader rotation, and wireless protocol interactions collectively influence system performance. Experimental results demonstrate that the proposed approach substantially reduces communication overhead without compromising control performance, significantly enhances fairness in over-the-air resource allocation, and incurs negligible impact on overall transportation capability.

Abstract

Multi robot teams performing cooperative transportation face a fundamental challenge: maintaining stable control while keeping communications efficient. This paper investigates how adaptive sampling time adjustment informed by measured network delay and strategic leader rotation can distribute wireless load fairly across the team. We use physics based simulation in MuJoCo with realistic wireless modeling, including time division multiple access, medium access control, jitter, queueing, and packet loss, to evaluate three control approaches: fixed sampling with static leadership, dynamic sampling with static leadership, and dynamic sampling with rotating leadership. Our results reveal an important trade off: dynamic sampling effectively reduces communications overhead without compromising control performance, while rotating the leader role meaningfully improves how fairly airtime is distributed all with negligible impact on the team carrying ability. to the best of our knowledge, being among the first to jointly examine dynamic sampling, rotating leadership, and wireless protocol interactions in physicsrealistic multi robot cooperation, this work provides practical guidance for deploying coordinated robotic teams in real world settings where communications resources are limited.

Problem

• cooperative transportation
• communication efficiency
• multi-robot systems
• wireless resource allocation
• control-communication trade-off

Innovation

• dynamic sampling
• rotating leadership
• TDMA
• multi-robot cooperation
• communication-control co-design