In this work, we propose a simulator, based on the open-source physics engine MuJoCo, for the design and control of soft robotic nets for the autonomous removal of space debris. The proposed simulator includes net dynamics, contact between the net and the debris, self-contact of the net, orbital mechanics, and a controller that can actuate thrusters on the four satellites at the corners of the net. It showcases the case of capturing Envisat, a large ESA satellite that remains in orbit as space debris following the end of its mission. This work investigates different mechanical models, which can be used to simulate the net dynamics, simulating various degrees of compliance, and different control strategies to achieve the capture of the debris, depending on the relative position of the net and the target. Unlike previous works on this topic, we do not assume that the net has been previously ballistically thrown toward the target, and we start from a relatively static configuration. The results show that a more compliant net achieves higher performance when attempting the capture of Envisat. Moreover, when paired with a sliding mode controller, soft nets are able to achieve successful capture in 100% of the tested cases, whilst also showcasing a higher effective area at contact and a higher number of contact points between net and Envisat.

翻译：本文基于开源物理引擎MuJoCo，提出了一种用于设计和控制自主清除太空碎片的软体机器人网的仿真器。该仿真器包含网动力学、网与碎片间的接触、网的自接触、轨道力学，以及一个可驱动网角四颗卫星推进器的控制器。本文展示了捕获Envisat的案例——这颗大型欧空局卫星在任务结束后仍作为太空碎片滞留轨道。研究探讨了可用于模拟网动力学的不同力学模型（模拟不同柔顺程度），以及根据网与目标的相对位置实现碎片捕获的不同控制策略。与先前关于该主题的研究不同，本文未假设网已通过弹道方式投向目标，而是从相对静态的初始构型出发。结果表明，在尝试捕获Envisat时，柔顺度更高的网性能更优。此外，结合滑模控制器后，软网在所有测试案例中均能实现100%的成功捕获，同时展现出更高的接触有效面积和更多的网-Envisat接触点。