Wang Jiahui, Zhang Yongbo, Zhu Shihao, Wang Junling
School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China.
Aircraft and Propulsion Laboratory, Ningbo Institute of Technology, Beihang University, Ningbo 315100, China.
Sensors (Basel). 2024 Nov 29;24(23):7663. doi: 10.3390/s24237663.
The three performance indexes of the space robot, travel time, energy consumption, and smoothness, are the key to its important role in space exploration. Therefore, this paper proposes a multi-objective trajectory planning method for robots. Firstly, the kinematics and dynamics of the Puma560 robot are analyzed to lay the foundation for trajectory planning. Secondly, the joint space trajectory of the robot is constructed with fifth-order B-spline functions, realizing the continuous position, velocity, acceleration, and jerk of each joint. Then, the improved multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the trajectory, and the distribution uniformity, convergence, and diversity of the obtained Pareto front are good. The improved MOPSO algorithm can realize the optimization between multiple objectives and obtain the trajectory that meets the actual engineering requirements. Finally, this paper implements the visualization of the robot's joints moving according to the optimal trajectory.
空间机器人的行程时间、能量消耗和平滑度这三个性能指标，是其在太空探索中发挥重要作用的关键。因此，本文提出了一种机器人多目标轨迹规划方法。首先，分析了Puma560机器人的运动学和动力学，为轨迹规划奠定基础。其次，用五阶B样条函数构建机器人的关节空间轨迹，实现各关节位置、速度、加速度和加加速度的连续。然后，采用改进的多目标粒子群优化（MOPSO）算法对轨迹进行优化，得到的帕累托前沿分布均匀性、收敛性和多样性良好。改进的MOPSO算法能够实现多目标之间的优化，获得满足实际工程需求的轨迹。最后，本文实现了机器人关节按最优轨迹运动的可视化。
