Predictive Reachability for Embodiment Selection in Mobile Manipulation Behaviors

TL;DR

This paper introduces a predictive reachability approach for embodiment selection in mobile manipulation, using a hierarchical world model to predict arm motions from image data, improving efficiency and performance over traditional inverse kinematics methods.

Contribution

The paper presents a novel predictive reachability method that leverages a world model for embodiment selection, eliminating the need for inverse kinematics and prior environment knowledge.

Findings

Outperforms previous model-based methods in sample efficiency.

Achieves better embodiment selection based on predicted reachability.

Demonstrates effectiveness across various environments.

Abstract

Mobile manipulators require coordinated control between navigation and manipulation to accomplish tasks. Typically, coordinated mobile manipulation behaviors have base navigation to approach the goal followed by arm manipulation to reach the desired pose. Selecting the embodiment between the base and arm can be determined based on reachability. Previous methods evaluate reachability by computing inverse kinematics and activate arm motions once solutions are identified. In this study, we introduce a new approach called predictive reachability that decides reachability based on predicted arm motions. Our model utilizes a hierarchical policy framework built upon a world model. The world model allows the prediction of future trajectories and the evaluation of reachability. The hierarchical policy selects the embodiment based on the predicted reachability and plans accordingly. Unlike methods that require prior knowledge about robots and environments for inverse kinematics, our method only relies on image-based observations. We evaluate our approach through basic reaching tasks across various environments. The results demonstrate that our method outperforms previous model-based approaches in both sample efficiency and performance, while enabling more reasonable embodiment selection based on predictive reachability.