TDMA Based Communications Control Co-Design for Cooperative Carrying: Delay Calibration and Sampling-Rate Optimization
2026-08-10 • Robotics
Robotics
AI summaryⓘ
The authors studied how teams of robots can carry things together while using their wireless communication more efficiently. They tested different ways to control the robots, including changing how often they send messages and switching which robot leads the team. Their findings show that adjusting message timing cuts down communication without hurting teamwork, and rotating the leader makes the wireless use fairer among robots. This helps in managing robot teams when wireless communication is limited.
multi-robot systemsadaptive samplingleader rotationwireless communicationmulti-access controlnetwork delayMuJoCo simulationcooperative transportationpacket lossdynamic sampling
Authors
Zahra Seifaei, Maximilian Luebke, Torsten Reissland, Danial Dehghani, Norman Franchi
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.