FORTE: Task-Adaptive Force Capability Optimization for Mobile Manipulators

2026-09-18

AI Summary

提出了一种针对冗余移动机械臂的任务自适应力能力优化框架，通过视觉-语言模型推断物体物理属性，并结合多目标轨迹优化，平衡了重载和轻载任务下的力能力和灵巧性。

Abstract

Effective physical interaction control in robotic manipulation requires not only kinematically feasible motion but also sufficient force-interaction capability. Existing redundancy resolution methods often ignore task-specific force demands or maximize the force capability indiscriminately, sacrificing dexterity when large force margins are unnecessary. We propose a task-oriented force capability optimization framework for redundant mobile manipulators. A Vision-Language Model (VLM) infers object physical properties from an RGB image and a task description, generating a desired task-force sequence that captures gravitational and inertial demands. We then define a task-oriented force capability metric as the signed distance between a task-force uncertainty ball and the dynamic residual force polytope (RFP), quantifying compatibility between task demands and the robot's remaining actuation capacity. This metric is incorporated, alongside manipulability, joint-limit avoidance, trajectory smoothness, and base-oscillation suppression, into a whole-body multi-objective trajectory-optimization problem. Experiments on a mobile manipulator performing lifting and single-point-holding tasks under varying payload conditions demonstrate that the proposed method provides sufficient force capability for heavy loads while preserving high manipulability for light loads. This yields a task-adaptive balance that fixed capability-maximizing baselines (RFP inscribed radius, RFP cone) and manipulability-only optimization fail to achieve. The core implementation is publicly available at https://github.com/yeying256/FORTE.

Problem

• robotic manipulation
• force capability
• redundancy resolution
• task-specific force demands
• manipulability

Innovation

• task-oriented force capability optimization
• Vision-Language Model (VLM)
• dynamic residual force polytope (RFP)
• multi-objective trajectory-optimization