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Trajectory Optimization Algorithm based on Robot Dynamics and Convex Optimization

机译:基于机器人动力学和凸优化的轨迹优化算法

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This paper mainly discusses the trajectory optimization problem of industrial robot along predetermined path in Cartesian space aiming at minimize the traverse time and smoothing the trajectory. The algorithm relies heavily on the complete robot dynamics model, in which both viscous friction and Coulomb friction are included. Based on convex optimization theory, the trajectory optimization formulation can transform into a second-order cone programming (SOCP) problem, which can be solved numerically through a discretization scheme and SDPT3 solver. Additionally, a constraint generated from the torque-speed curve of motors is added to the aforementioned convex optimization formulation. The simulation results show that our improved trajectory optimization algorithm attains smooth and time optimal trajectory with shorter traverse time and good tracking performance compared with previous methods.
机译:本文主要讨论了笛卡尔空间中工业机器人在预定路径上的轨迹优化问题,旨在最小化轨迹时间并平滑轨迹。该算法在很大程度上依赖于完整的机器人动力学模型,其中包括了粘滞摩擦和库仑摩擦。基于凸优化理论,轨迹优化公式可以转化为二阶锥规划(SOCP)问题,可以通过离散化方案和SDPT3求解器对其进行数值求解。另外,将从电动机的转矩-速度曲线产生的约束添加到上述凸优化公式中。仿真结果表明,与以前的方法相比,改进后的轨迹优化算法可以实现平滑,时间最优的轨迹,且轨迹时间短,跟踪性能好。

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