HiTMap: A Hierarchical Topological Map Representation for Navigation in Unknown Environments
This addresses the challenge of drift and scalability in map representations for mobile robots, though it appears incremental as it enhances existing methods rather than introducing a new paradigm.
The paper tackles the problem of autonomous navigation in unknown environments by proposing HiTMap, a hierarchical topological map representation that uses submaps and frontiers to reduce reliance on global metric maps, validated in simulation and real-world with open-source availability.
The ability to autonomously navigate in unknown environments is important for mobile robots. The map is the core component to achieve this. Most map representations rely on drift-free state estimation and provide a global metric map to navigate. However, in large-scale real-world applications, it's hard to prohibit drifts and compose a globally consistent map quickly. In this paper, a novel representation named, HiTMap, is proposed to enhance the existing map representations. The central idea is to adopt a submap-based hierarchical topology rather than a global metric map so that only a local metric map is maintained for obstacle avoidance which ensures the lightweight of the representation. To guide the robots navigate into unknown spaces, frontiers are detected and attached to the map as an attribute. We also develop a path planning module to evaluate the feasibility and efficiency of our map representation. The system is validated in a simulation environment and a demonstration in the real world is conducted. In addition, the HiTMap is made available open-source.