Autonomous Exploration with Terrestrial-Aerial Bimodal Vehicles

Abstract

Terrestrial-aerial bimodal vehicles, which integrate the high mobility of aerial robots with the long endurance of ground robots, offer significant potential for autonomous exploration. Given the inherent energy and time constraints in practical exploration tasks, we present a hierarchical framework for the bimodal vehicle to utilize its flexible locomotion modalities for exploration. Beginning with extracting environmental information to identify informative regions, we generate a set of potential bimodal viewpoints. To adaptively manage energy and time constraints, we introduce an extended Monte Carlo Tree Search approach that strategically optimizes both modality selection and viewpoint sequencing. Combined with an improved bimodal vehicle motion planner, we present a complete bimodal energy- and time-aware exploration system. Extensive simulations and deployment on a customized real-world platform demonstrate the effectiveness of our system.

Tiancheng Lai 赖天成

Master

My research interests focus on Motion Planning, Autonomous Exploration, etc.

Yanjun Cao 曹燕军

Research Professor

My research interests focuse on key challenges in multi-robot systems, such as collaborative localization, perception, communication, and system organization.

Chao Xu 许超

Full Professor

My research interests include Geometries and Control of Mechanical Systems, Kinematic Agents and Cybernetics, Multi-Physics Driven Robotics, AI-Driven Science.

Fei Gao 高飞

Associate Professor

My research interests include aerial robotics, autonomous navigation, swarm cooperation, and embodied intelligence.