We present Ruckig, an algorithm for Online Trajectory Generation (OTG) respecting third-order constraints and complete kinematic target states. Given any initial state of a system with multiple Degrees of Freedom (DoFs), Ruckig calculates a time-optimal trajectory to an arbitrary target state defined by its position, velocity, and acceleration limited by velocity, acceleration, and jerk constraints. The proposed algorithm and implementation allows three contributions: (1) To the best of our knowledge, we derive the first time-optimal OTG algorithm for arbitrary, multi-dimensional target states, in particular including non-zero target acceleration. (2) This is the first open-source prototype of time-optimal OTG with limited jerk and complete time synchronization for multiple DoFs. (3) Ruckig allows for directional velocity and acceleration limits, enabling robots to better use their dynamical resources. We evaluate the robustness and real-time capability of the proposed algorithm on a test suite with over 1,000,000,000 random trajectories as well as in real-world applications.
翻译:我们提出了Ruckig, 在线轨迹生成算法(OtG), 它符合三阶限制和完整的运动目标状态。考虑到一个具有多度自由的系统(DoFs)的任何初始状态, Ruckig计算出一个时间最佳的轨迹, 达到一个任意的目标状态, 其位置、 速度和加速度由速度、 加速度和自动限制所限定。 提议的算法和实施允许三种贡献:(1) 根据我们的最佳知识, 我们为任意、 多维目标状态, 特别是包括非零目标加速度, 得出第一个最佳的 OtG算法。 (2) 这是第一个开放源的OtG原型, 其时最佳和完整时间同步性有限, 使多度DoFs 。 (3) Ruckig允许方向速度和加速极限, 使机器人能够更好地利用其动态资源。 我们评估了1,000 000 000多随机轨迹以及实际应用的测试套件上拟议算法的坚固性和实时能力。