Multi-Floor Exploration for Ground Robots via an Incremental Reachable Graph and Structural Priors
Zhiwen Zhu, Jiaqi Chen, Xiangyi Huang, Meiqi Hu, Boyu Zhou
2026
Abstract
Autonomous exploration of multi-floor buildings remains challenging for ground robots because conventional 2D and 2.5D maps cannot represent overlapping traversable surfaces such as stairs, ramps, and multiple reachable elevations. This letter presents a multi-floor exploration framework based on an incremental reachable graph. Built as a sparse graph over reachable support surfaces, the graph preserves potentially valid connectivity through tentative graph elements under sparse observations and enables stable, physically reachable frontier detection. To guide exploration beyond the currently mapped floor, we project task-zone priors from an explored floor to initialize a hypothetical graph on the target floor and reconcile it incrementally with incoming observations. A hierarchical planner then jointly reasons over confirmed and hypothetical structures for global guidance. In simulation, the proposed method demonstrates improved exploration efficiency and mapping completeness compared to evaluated baselines. Furthermore, onboard real-world experiments validate its practical feasibility and real-time performance.
Keywords
Related papers
Trajectory tracking control for 6WID/4WIS UGV via nonlinear sliding mode-model predictive control with adaptive following steering and dynamic-static constraints
Shengyang Lu, Guanpeng Chen, Lijing Zhao +2 more
Robotics and Autonomous Systems · 2026
Bioinspired underwater robotics: Advances across the materials, design, control, and applications
Dilip Muchhala, Pramod Kumar Maurya, Adarsh Raut +3 more
Robotics and Autonomous Systems · 2026
Artificial pushing adaptive coordinated control for the human-exoskeleton-walker system
Xinhao Zhang, Chen Yang, Chaobin Zou +4 more
Robotics and Autonomous Systems · 2026
Modeling and control of a rigid–soft hybrid-link humanoid robot
Zewen He, Taiki Ishigaki, Ko Yamamoto
Robotics and Autonomous Systems · 2026