RobotOBchain: Neighbor Observation for Byzantine Detection in Multi-Robot Systems

Multi-robot systems are increasingly deployed in critical applications such as search and rescue, precision agriculture, and autonomous transportation. However, the presence of Byzantine robots—agents that intentionally transmit false or misleading information—can severely compromise mission success and system safety, highlighting the urgent need for robust fault-tolerant coordination mechanisms. To address the challenge of Byzantine faults in multi-robot systems, we propose a novel approach utilizing a blockchain-based framework, termed RobotOBchain (Robot Observation Blockchain). RobotOBchain permanently records each robot’s own state information and its observed neighboring robots’ states at every time step. By leveraging smart contracts encoded within the blockchain, our method automatically detects state inconsistencies or conflicts among recorded observations, enabling early identification of intentionally deceptive Byzantine robots. Experimental validation demonstrates that RobotOBchain achieves 100% consistent Byzantine identification across all robots, maintains estimation errors within 3% of ground-truth, and exhibits robust tolerance to up to 50% malicious agents. These results significantly surpass the performance of classical W-MSR algorithms, while eliminating the dependency on predefined fault bounds. The framework’s demonstrated capabilities indicate strong potential for practical deployment in dynamic and safety-critical multi-robot applications.