This paper presents a multi-contact motion adaptation framework that enables teleoperation of high degree-of-freedom (DoF) robots, such as quadrupeds and humanoids, for loco-manipulation tasks in multi-contact settings. Our proposed algorithms optimize whole-body configurations and formulate the retargeting of multi-contact motions as sequential quadratic programming, which is robust and stable near the edges of feasibility constraints. Our framework allows real-time operation of the robot and reduces cognitive load for the operator because infeasible commands are automatically adapted into physically stable and viable motions on the robot. The results in simulations with full dynamics demonstrated the effectiveness of teleoperating different legged robots interactively and generating rich multi-contact movements. We evaluated the computational efficiency of the proposed algorithms, and further validated and analyzed multi-contact loco-manipulation tasks on humanoid and quadruped robots by reaching, active pushing and various traversal on uneven terrains.
翻译:本文介绍一个多接触运动适应框架,使高自由度机器人(DoF)的远程操作,如四重机器人和人类类机器人,能够在多接触环境中执行loco管理任务。我们提议的算法优化了整个身体配置,并将多接触运动的重新定位作为连续的二次方程式,这种程序在可行性制约的边缘是稳健和稳定的。我们的框架允许机器人的实时操作,并减少操作者的认知负荷,因为不可行的命令会自动适应在机器人上的实际稳定和可行的动作。具有充分动态的模拟结果表明,通过互动和产生丰富的多接触运动,远程操作不同的腿机器人是有效的。我们评估了拟议算法的计算效率,并通过在不均匀的地形上接触、积极推动和各种曲解,进一步验证和分析了人类和四重机器人的多接触操作任务。