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Bringing Network Coding into Multi-Robot Systems: Interplay Study for Autonomous Systems over Wireless Communications

Anil Zaher, Kiril Solovey, Alejandro Cohen

Abstract

Communication is a core enabler for multi-robot systems (MRS), providing the mechanism through which robots exchange state information, coordinate actions, and satisfy safety constraints. While many MRS autonomy algorithms assume reliable and timely message delivery, realistic wireless channels introduce delay, erasures, and ordering stalls that can degrade performance and compromise safety-critical decisions of the robot task. In this paper, we investigate how transport-layer reliability mechanisms that mitigate communication losses and delays shape the autonomy-communication loop. We show that conventional non-coded retransmission-based protocols introduce long delays that are misaligned with the timeliness requirements of MRS applications, and may render the received data irrelevant. As an alternative, we advocate for adaptive and causal network coding, which proactively injects coded redundancy to achieve the desired delay and throughput that enable relevant data delivery to the robotic task. Specifically, this method adapts to channel conditions between robots and causally tunes the communication rates via efficient algorithms. We present two case studies: cooperative localization under delayed and lossy inter-robot communication, and a safety-critical overtaking maneuver where timely vehicle-to-vehicle message availability determines whether an ego vehicle can abort to avoid a crash. Our results demonstrate that coding-based communication significantly reduces in-order delivery stalls, preserves estimation consistency under delay, and improves deadline reliability relative to retransmission-based transport. Overall, the study highlights the need to jointly design autonomy algorithms and communication mechanisms, and positions network coding as a principled tool for dependable multi-robot operation over wireless networks.

Bringing Network Coding into Multi-Robot Systems: Interplay Study for Autonomous Systems over Wireless Communications

Abstract

Communication is a core enabler for multi-robot systems (MRS), providing the mechanism through which robots exchange state information, coordinate actions, and satisfy safety constraints. While many MRS autonomy algorithms assume reliable and timely message delivery, realistic wireless channels introduce delay, erasures, and ordering stalls that can degrade performance and compromise safety-critical decisions of the robot task. In this paper, we investigate how transport-layer reliability mechanisms that mitigate communication losses and delays shape the autonomy-communication loop. We show that conventional non-coded retransmission-based protocols introduce long delays that are misaligned with the timeliness requirements of MRS applications, and may render the received data irrelevant. As an alternative, we advocate for adaptive and causal network coding, which proactively injects coded redundancy to achieve the desired delay and throughput that enable relevant data delivery to the robotic task. Specifically, this method adapts to channel conditions between robots and causally tunes the communication rates via efficient algorithms. We present two case studies: cooperative localization under delayed and lossy inter-robot communication, and a safety-critical overtaking maneuver where timely vehicle-to-vehicle message availability determines whether an ego vehicle can abort to avoid a crash. Our results demonstrate that coding-based communication significantly reduces in-order delivery stalls, preserves estimation consistency under delay, and improves deadline reliability relative to retransmission-based transport. Overall, the study highlights the need to jointly design autonomy algorithms and communication mechanisms, and positions network coding as a principled tool for dependable multi-robot operation over wireless networks.
Paper Structure (11 sections, 5 equations, 4 figures, 2 tables)

This paper contains 11 sections, 5 equations, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Background on Communication Systems
  3. Transport Protocols
  4. Communication Challenges in Multi-Robot Systems
  5. System Models and Case Studies
  6. Cooperative Localization
  7. Safety-Critical Overtaking Under Timing Constraints
  8. Experimental Setup and Results
  9. Cooperative Localization Results
  10. Safety-Critical Overtaking Results
  11. Discussion and Future Work

Figures (4)

  • Figure 1: Illustraion of a cooperative localization scenario, which we consider in our first case study (see Sec. \ref{['subsec:coopL']} and \ref{['subsec:cooploc_results']}). Each robot obtains local GPS-like measurements and inter-robot measurements of nearby robots, which are shared over inter-robot communication channel. The colored curves show the robots' ground-truth trajectories, while the arrows depict the communicated inter-robot observations. Arrow thickness and color intensity encode the communicated measurement delay (darker and thicker arrows indicate larger delays).
  • Figure 2: Visualization of the overtaking scenario we consider in our second case study (see Sections \ref{['subsec:overtake_model']} and \ref{['subsec:overtake_results']}) with an initial configuration, and two separate runs using AC-RLNC and SR-ARQ transport mechanisms, respectively. Ego vehicle $A$ (red) follows the outer lane behind truck $T$ (yellow), while oncoming vehicle $B$ (green) approaches from the opposite direction on the same lane. Timely V2V packet reception is required for $A$ to detect the oncoming hazard and abort. Blue dots indicate time instants at which V2V packets from vehicle $B$ are successfully received by the ego vehicle $A$.
  • Figure 3: Cooperative localization estimation error under different communication conditions, transport protocols, and delivery delays. Here $\epsilon$ denotes the packet erasure probability. "No Dly" denotes $\mathrm{RTT}=0$, while "one-way Dly" denotes a fixed one-way delay of $\mathrm{RTT}/2$. "No I-ReE" corresponds to the naive approach that updates the EKF upon packet arrival, while "I-ReE" denotes the delay-aware iterative re-estimation method. For reliable protocols, packets additionally experience protocol-dependent in-order delivery delay due to retransmissions (SR-ARQ) or decoding (AC-RLNC). Curves without a protocol name correspond to the estimator-only comparison under the stated delay/erasure condition.
  • Figure 4: Overtaking reliability--latency function $\Pr[T_{25} \le t]$, where $t$ (horizontal axis) denotes time slots and $T_{25}$ is the arrival time of the 25th successfully received packet. The value at $t=110$ corresponds to the probability of satisfying the abort-by-deadline requirement.