Manipulating deformable objects arises in daily life and numerous applications. Despite phenomenal advances in industrial robotics, manipulation of deformable objects remains mostly a manual task. This is because of the high number of internal degrees of freedom and the complexity of predicting its motion. In this paper, we apply the computationally efficient position-based dynamics method to predict object motion and distance to obstacles. This distance is incorporated in a control barrier function for the resolved motion kinematic control for one or more robots to adjust their motion to avoid colliding with the obstacles. The controller has been applied in simulations to 1D and 2D deformable objects with varying numbers of assistant agents, demonstrating its versatility across different object types and multi-agent systems. Results indicate the feasibility of real-time collision avoidance through deformable object simulation, minimizing path tracking error while maintaining a predefined minimum distance from obstacles and preventing overstretching of the deformable object. The implementation is performed in ROS, allowing ready portability to different applications.

翻译：可变形物体的操作在日常生活和众多应用中普遍存在。尽管工业机器人技术取得了显著进步，但可变形物体的操作仍主要依赖人工完成。这是由于此类物体具有大量内部自由度，且其运动预测复杂。本文采用计算高效的位置动力学方法预测物体运动及其与障碍物的距离。将该距离纳入控制障碍函数中，用于单台或多台机器人的运动学控制，以调整其运动避免与障碍物碰撞。该控制器已应用于一维和二维可变形物体的仿真实验，并测试了不同数量的辅助智能体，验证了其在不同物体类型和多智能体系统中的通用性。结果表明，通过可变形物体仿真可实现实时避障，在保持与障碍物预设最小距离并防止物体过度拉伸的同时，最小化路径跟踪误差。该实现基于ROS系统，可便捷地移植至不同应用场景。