Whole-Body Control With Terrain Estimation of A 6-DoF Wheeled Bipedal Robot
🤖 AI Summary
Wheel-legged bipedal robots suffer from motion control limitations on uneven terrain due to oversimplified leg dynamics modeling and idealized flat-ground assumptions. To address this, we propose a holistic dynamic framework integrating leg-arm dynamics with a wheel–terrain contact model. We further develop a real-time terrain perception method leveraging LiDAR-inertial odometry and an improved PCA-based point cloud normal estimation. A closed-chain dynamics-driven hierarchical controller is designed: a low-level PD/LQR controller regulates body attitude and center-of-mass balance, while a high-level multi-task prioritization optimizer coordinates whole-body motions. Our approach overcomes conventional modeling simplifications, enabling stable locomotion and high-fidelity terrain adaptation on unstructured surfaces—including slopes and stairs. Simulation and hardware experiments validate the method’s efficacy: terrain normal estimation achieves mean angular error <3.2°, and the hierarchical controller demonstrates robust whole-body coordination under dynamic terrain constraints.
Application Category
📝 Abstract
Wheeled bipedal robots have garnered increasing attention in exploration and inspection. However, most research simplifies calculations by ignoring leg dynamics, thereby restricting the robot's full motion potential. Additionally, robots face challenges when traversing uneven terrain. To address the aforementioned issue, we develop a complete dynamics model and design a whole-body control framework with terrain estimation for a novel 6 degrees of freedom wheeled bipedal robot. This model incorporates the closed-loop dynamics of the robot and a ground contact model based on the estimated ground normal vector. We use a LiDAR inertial odometry framework and improved Principal Component Analysis for terrain estimation. Task controllers, including PD control law and LQR, are employed for pose control and centroidal dynamics-based balance control, respectively. Furthermore, a hierarchical optimization approach is used to solve the whole-body control problem. We validate the performance of the terrain estimation algorithm and demonstrate the algorithm's robustness and ability to traverse uneven terrain through both simulation and real-world experiments.
Problem
Research questions and friction points this paper is trying to address.
Develops whole-body control for 6-DoF wheeled bipedal robot dynamics
Enables traversal on uneven terrain through ground estimation
Solves motion limitations by incorporating leg and contact dynamics
Innovation
Methods, ideas, or system contributions that make the work stand out.
Developed complete dynamics model with terrain estimation
Used LiDAR inertial odometry for ground normal estimation
Implemented hierarchical optimization for whole-body control
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