Controlling the shape of deformable linear objects using robots and constraints provided by environmental fixtures has diverse industrial applications. In order to establish robust contacts with these fixtures, accurate estimation of the contact state is essential for preventing and rectifying potential anomalies. However, this task is challenging due to the small sizes of fixtures, the requirement for real-time performances, and the infinite degrees of freedom of the deformable linear objects. In this paper, we propose a real-time approach for estimating both contact establishment and subsequent changes by leveraging the dependency between the applied and detected contact force on the deformable linear objects. We seamlessly integrate this method into the robot control loop and achieve an adaptive shape control framework which avoids, detects and corrects anomalies automatically. Real-world experiments validate the robustness and effectiveness of our contact estimation approach across various scenarios, significantly increasing the success rate of shape control processes.

翻译：利用机器人及环境夹具提供的约束来控制可变形线性物体的形状具有广泛的工业应用。为了与这些夹具建立稳健的接触，准确估计接触状态对于预防和纠正潜在异常至关重要。然而，由于夹具尺寸小、实时性要求高以及可变形线性物体具有无限自由度，这项任务颇具挑战性。本文提出一种实时方法，通过利用施加于可变形线性物体的接触力与检测到的接触力之间的依赖关系，来估计接触建立及后续接触变化。我们将该方法无缝集成到机器人控制回路中，实现了一种自适应形状控制框架，能够自动避免、检测并纠正异常。实际实验验证了我们的接触估计方法在各种场景下的鲁棒性和有效性，显著提高了形状控制过程的成功率。