2024/09/20 by Dharshan Bashkaran Latha, Latha, Dharshan Bashkaran, Ömür Arslan +1
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · #68T40 #68T45 #93B52 #DNA and Biological Computing #FOS: Computer and information sciences #FOS: Electrical engineering #I.2.10 #I.2.8 #I.2.9 #Modular Robots and Swarm Intelligence #Optimization and Search Problems #Robotics (cs.RO) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2409.13838
openalex publication_date 2024/09/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Safe autonomous navigation in a priori unknown environments is an essential skill for mobile robots to reliably and adaptively perform diverse tasks (e.g., delivery, inspection, and interaction) in unstructured cluttered environments. Hybrid metric-topological maps, constructed as a pose graph of local submaps, offer a computationally efficient world representation for adaptive mapping, planning, and control at the regional level. In this paper, we consider a pose graph of locally sensed star-convex scan regions as a metric-topological map, with star convexity enabling simple yet effective local navigation strategies. We design a new family of safe local scan navigation policies and present a perception-driven feedback motion planning method through the sequential composition of local scan navigation policies, enabling provably correct and safe robot navigation over the union of local scan regions. We introduce a new concept of bridging and frontier scans for automated key scan selection and exploration for integrated mapping and navigation in unknown environments. We demonstrate the effectiveness of our key-scan-based navigation and mapping framework using a mobile robot equipped with a 360∘ laser range scanner in 2D cluttered environments through numerical ROS-Gazebo simulations and real hardware~experiments.