We present NEO, a fast and purely reactive motion controller for manipulators which can avoid static and dynamic obstacles while moving to the desired end-effector pose. Additionally, our controller maximises the manipulability of the robot during the trajectory, while avoiding joint position and velocity limits. NEO is wrapped into a strictly convex quadratic programme which, when considering obstacles, joint limits, and manipulability on a 7 degree-of-freedom robot, is generally solved in a few ms. While NEO is not intended to replace state-of-the-art motion planners, our experiments show that it is a viable alternative for scenes with moderate complexity while also being capable of reactive control. For more complex scenes, NEO is better suited as a reactive local controller, in conjunction with a global motion planner. We compare NEO to motion planners on a standard benchmark in simulation and additionally illustrate and verify its operation on a physical robot in a dynamic environment. We provide an open-source library which implements our controller.
翻译:我们提出了近地物体,它是一个能避免静态和动态障碍的操纵器的快速和纯反应式运动控制器,它能避免静态和动态障碍,同时移动到理想的终端效应姿势。此外,我们的控制器在轨迹期间最大限度地扩大了机器人的操纵力,同时避免了联合位置和速度限制。近地物体被包裹在一个严格的锥形二次方案中,在考虑障碍、联合界限和7度自由机器人的可操作性时,一般会在几米内解决。虽然近地物体不打算取代最先进的运动规划器,但我们的实验表明,它对于中度复杂场景来说是一种可行的替代方法,同时也能够进行反应控制。对于更复杂的场景,近地物体更适合作为反应性的地方控制器,同时结合一个全球运动规划器。我们比较近地物体,以模拟的标准基准来移动规划者,并额外说明和核查其在动态环境中的物理机器人的操作情况。我们提供了一个执行控制器的开放源图书馆。