论文标题
NEO：一种新型的快速优化算法，用于操纵器的反应性运动控制
NEO: A Novel Expeditious Optimisation Algorithm for Reactive Motion Control of Manipulators
论文作者
论文摘要
我们提出了Neo，这是一种用于操纵器的快速而纯粹的反应性运动控制器，可以在移动到所需的最终效果姿势时避免静态和动态障碍物。此外，我们的控制器在轨迹期间最大化机器人的可操作性，同时避免了关节位置和速度极限。 NEO被包裹在一个严格的凸二次程序中，该程序在考虑障碍物，关节限制和可操作性时，通常在几个MS中就可以解决。尽管NEO并不是要替代最新的运动计划者，但我们的实验表明，对于具有中等复杂性的场景，同时也能够反应性控制，它是可行的替代方法。对于更复杂的场景，Neo与全球运动计划者结合使用，更适合作为反应性本地控制器。我们将NEO与Motion Planners在模拟中的标准基准上进行比较，并在动态环境中说明并验证其在物理机器人上的操作。我们提供一个开源库来实现我们的控制器。
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.
