Low-Bandwidth Adaptive Human-Machine Collaboration Technology for Small Indoor Robots

As urban centers continue to expand, the complexity of post-disaster rescue operations in such environments is exacerbated by intricate terrain and compromised communication networks. While ground robots have been instrumental in mitigating risks for human rescuers, their effectiveness is often limited by a heavy reliance on robust communication links for remote control. To enhance the operational range of ground robots in such disaster-stricken urban areas, we introduce a low-bandwidth adaptive human-machine collaboration system. The effective control of the ground robot under non-ideal communication conditions is achieved through a hierarchical human-machine interaction model and a low-bandwidth-dependent polygonal semantic map construction method. The effectiveness of the technique is validated through practical experiments. The experimental results show that this technology is based on the principle of human-machine collaboration, leveraging both human intelligence and machine intelligence. It enables autonomous interaction and cooperative operation between humans and robots in complex unknown urban scenes, providing crucial support for urban disaster rescue operations.