Contact as a Decision Variable: Capability-Tradeoff Contact Selection for Legged Loco-Manipulation

Summary

Abstract Summary

In this paper, we study the joint selection of an environmental support contact and a whole-body configuration for a prescribed loco-manipulation task. A contact may provide greater physical support while restricting the motion required for the task. We formulate this problem through three capability measures: residual wrench, end-effector reach, and base mobility available after satisfying the task requirements, and we balance them against contact acquisition cost. Evaluating these capabilities for every candidate requires repeated whole-body optimizations. To reduce this computational cost, we propose Capability-Tradeoff Contact Selection (CTCS). CTCS screens candidates for contact and task feasibility, groups similar candidates within each surface, and predicts their capabilities from exact anchor evaluations using local sensitivity analysis. It checks these predictions through selective exact evaluations, ranks candidates by capability, and evaluates a shortlist exactly for final selection. We evaluate CTCS in simulations and hardware experiments using a Unitree Go2 quadruped with an AgileX NERO arm across $392$ task conditions with nine available support surfaces. Results show that CTCS outperforms ground-only and fixed-contact support, as it can select support surfaces that provide favorable capability trade-offs for the task. Compared with evaluating every candidate exactly, CTCS achieves approximately $3\times$ speedup while closely matching the resulting mean objective value.

Key Points

In this paper, we study the joint selection of an environmental support contact and a whole-body configuration for a prescribed loco-manipulation task.
A contact may provide greater physical support while restricting the motion required for the task
We formulate this problem through three capability measures: residual wrench, end-effector reach, and base mobility available after satisfying the task requirements, and we balance them against contact acquisition cost.
Evaluating these capabilities for every candidate requires repeated whole-body optimizations
To reduce this computational cost, we propose Capability-Tradeoff Contact Selection (CTCS)

Literature Review

Legged mobile manipulators typically rely on stance-foot contacts for whole-body support [ 6 , 7 , 8 , 9 ] . Additional contacts with environmental structures have also been investigated for humanoid and legged robots [ 10 , 11 ] , as hand and body contacts with environments can help humanoid robots maintain or recover balance under disturbances [ 12 , 13 , 14 ] .

Preliminaries and Problem Formulation

We consider a quadruped mobile manipulator that can use environmental surfaces as additional physical support during a loco-manipulation task. Our objective is to select an environmental contact and whole-body configuration that satisfy the task’s load and motion requirements while providing a favorable trade-off among the capabilities available under the task load.

We first introduce the robot and contact models, then define the task requirements and capability measures, and finally formulate the joint selection problem.

Preliminaries and Problem Formulation — Contact as a Decision Variable: Capability-Tradeoff Contact Selection for Legged Loco-Manipulation — Fig. 3: Examples of different environmental surfaces and the corresponding contact realization of the mobile manipulator.

Methodology

Evaluating the capability vector $\xi(\chi)$ exactly for every candidate requires solving many whole-body optimization problems across the task-applicable capabilities and stance phases. To address this, we propose Capability-Tradeoff Contact Selection (CTCS), which combines exact feasibility screening, local sensitivity-based capability prediction, and selective exact evaluation. As visualized in Fig.

Experiments and Results

We evaluate CTCS on a quadruped mobile manipulator in environments where multiple support surfaces are available. We assess the contact selection quality, computational cost, and task performance, and compare them with baselines. The validation is performed on both Gazebo simulations and hardware experiments. Hardware and Environment Setup.

We use a Unitree Go2 quadruped equipped with an AgileX NERO 7-DoF manipulator and a rigid planar support frame mounted on the side of its body for establishing environmental contact (Fig. 1 ).

Experiments and Results — Contact as a Decision Variable: Capability-Tradeoff Contact Selection for Legged Loco-Manipulation — Fig. 5: Hardware experiment. Upper: A sticking-mode manipulation task with an applied downward force while maintaining selected support contact. Lower: A walking task. The robot sustains the applied force while maintaining the sliding support contact, closely tracking the required base velocity and end-effector position.

Sources and Demonstrations

Figures are reproduced from Mahmud et al. See the full paper for experimental details and the project page, when the paper links one, for demonstrations and videos.