ROJun 17

Mobile Pedipulation for Object Sliding via Hierarchical Control on a Wheeled Bipedal Robot

arXiv:2606.192332.9
Predicted impact top 88% in RO · last 90 daysOriginality Incremental advance
AI Analysis

It enables wheeled bipedal robots to manipulate objects via pedipulation, expanding their capabilities for tasks in cluttered environments.

This paper presents a hierarchical control framework for wheeled bipedal robots to perform planar object sliding using their legs. The approach was validated on hardware, achieving object retrieval of a 1 kg object and sliding a 4 kg object over 0.228 m.

In this letter, we present a hierarchical control framework that enables wheeled bipedal robots to perform planar object sliding tasks with their wheeled legs. The proposed approach formulates a nonlinear model predictive controller (NMPC) based on a reduced-order three rigid bodies (TRB) dynamical model that explicitly accounts for the hip roll degree of freedom and multiple wheel-environment contact modes, which is essential for lateral stepping and pedipulation tasks. Within this framework, the NMPC simultaneously regulates robot locomotion and interaction forces, allowing the robot to stably execute both rolling and object manipulation behaviors. A trajectory-optimization-based robot-object motion planner is developed to generate reference motions that incorporate stick-slip transitions in ground-object contact. Two representative pedipulation motions, namely scooting and lateral sliding, are validated through real-world hardware experiments, in which the robot successfully retrieves a 1 kg object from under a desk and slides a 4 kg object over a distance of 0.228 m via scooting.

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