Portable Planner for Enhancing Ground Robots Exploration Performance in Unstructured Environments

摘要

In this letter, we present a novel portable strategy for the autonomous exploration of highly unstructured three-dimensional environments using ground robots. The proposed planner leverages elevation mapping to estimate traversability, enabling efficient environment mapping while conserving computational resources and preserving essential information. We maintain the state of map vertices using a fuzzy finite state machine, ensuring that the map encompasses only accessible areas for ground robots and simplified obstacles. This approach effectively realizes a multi-level hierarchical framework, allowing the incorporation of multiple factors into exploration gain design. Additionally, we have implemented an emergency response mechanism to balance obstacle avoidance and computational efficiency. Our method has been rigorously tested in both simulation and real-world scenarios on wheeled and legged robots, achieving task completeness rates exceeding 90%, outperforming existing approaches in complex environments. Furthermore, we have open-sourced our method, promoting collaboration and advancement in the field of ground robot exploration.