arXiv:2506.16555cs.ROcs.SY2025-06中稿 · oral presentation …被引 3

融合力控与优化规划,实现多机械臂灵巧操作的无缝切换。

An Optimization-Augmented Control Framework for Single and Coordinated Multi-Arm Robotic Manipulation

  • 分任务动态选择优化、力控或混合控制模式
  • 支持长时序操作,兼顾自由空间运动与接触交互
  • 适合双臂及多臂协同,提升协调性与鲁棒性

机器人操作需精确控制接触力与运动轨迹。力控制适用于近距离高频率适应,但难以维持长时间运动中的稳定姿态;优化规划擅长生成无碰撞的全局轨迹,却难以处理动态接触场景。为此,我们提出一种多模态控制框架,将力控制与优化增强型运动规划相结合,按任务需求顺序切换控制模式。方法将复杂任务分解为子任务,动态分配至三种模式:纯优化用于全局规划,纯力控用于精细交互,混合控制用于需同步轨迹跟踪与力调节的任务。该框架特别适用于双臂及多臂操作,确保各臂间同步协调,同时满足物体与环境约束。我们在单臂、双臂和多臂任务中验证了方法的通用性,展示了其在自由空间运动与高接触密度操作中兼具鲁棒性与精度的能力。

原文摘要 · Abstract (English)

Robotic manipulation demands precise control over both contact forces and motion trajectories. While force control is essential for achieving compliant interaction and high-frequency adaptation, it is limited to operations in close proximity to the manipulated object and often fails to maintain stable orientation during extended motion sequences. Conversely, optimization-based motion planning excels in generating collision-free trajectories over the robot's configuration space but struggles with dynamic interactions where contact forces play a crucial role. To address these limitations, we propose a multi-modal control framework that combines force control and optimization-augmented motion planning to tackle complex robotic manipulation tasks in a sequential manner, enabling seamless switching between control modes based on task requirements. Our approach decomposes complex tasks into subtasks, each dynamically assigned to one of three control modes: Pure optimization for global motion planning, pure force control for precise interaction, or hybrid control for tasks requiring simultaneous trajectory tracking and force regulation. This framework is particularly advantageous for bimanual and multi-arm manipulation, where synchronous motion and coordination among arms are essential while considering both the manipulated object and environmental constraints. We demonstrate the versatility of our method through a range of long-horizon manipulation tasks, including single-arm, bimanual, and multi-arm applications, highlighting its ability to handle both free-space motion and contact-rich manipulation with robustness and precision.

机器人控制多臂协作力控运动规划

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