In noncontact machining, such as welding and spraying, running efficiency and smoothness have been a bottleneck problem in trajectory optimisation of industrial robots. When the dynamic and mechanical properties of robots are fully utilised, significant impact are often produced. Thus, reducing the process impact of the robot and achieving a balance between the efficiency and smoothness of the operation process are complex problems that need to be solved. The trajectory optimisation problem is modelled based on the excellent properties of the convex-optimization (CO) problem. CO parameters were introduced to solve the inconsistency between the constrained and planned spaces. To obtain the weight factor of the multi-objective optimisation problem, a multi-objective adaptive optimisation method was proposed to select the optimal parameters. Aiming at the large process impact of the optimisation problem, which considers running time as the main optimisation objective, an acceleration continuity constraint method was proposed based on the smoothing path. Finally, the objective optimisation problem was transformed into a standardised second-order cone programming problem to complete the solution. The experimental results show that the proposed method can improve the robot operation efficiency and reduce the process impact by approximately 26% and 22%, respectively, from three aspects: optimum time, balance between efficiency and impact, and acceleration continuity.

在焊接、喷涂等非接触加工中，运行效率和平稳性一直是工业机器人轨迹优化的瓶颈问题。当机器人的动态和机械特性得到充分利用时，往往会产生显着的影响。因此，降低机器人的过程影响，实现作业过程的效率与流畅性的平衡，是需要解决的复杂问题。轨迹优化问题是基于凸优化 (CO) 问题的优良特性建模的。CO 参数的引入是为了解决受限空间和规划空间之间的不一致问题。为了获得多目标优化问题的权重因子，提出了一种多目标自适应优化方法来选择最优参数。针对以运行时间为主要优化目标的优化问题过程影响大的问题，提出了一种基于平滑路径的加速度连续性约束方法。最后将目标优化问题转化为标准化的二阶锥规划问题完成求解。实验结果表明，所提方法从最佳时间、效率与冲击的平衡、加速连续性三个方面分别提高了机器人运行效率，减少了约26%和22%的过程冲击。将目标优化问题转化为标准化的二阶锥规划问题完成求解。实验结果表明，所提方法从最佳时间、效率与冲击的平衡、加速连续性三个方面分别提高了机器人运行效率，减少了约26%和22%的过程冲击。将目标优化问题转化为标准化的二阶锥规划问题完成求解。实验结果表明，所提方法从最佳时间、效率与冲击的平衡、加速连续性三个方面分别提高了机器人运行效率，减少了约26%和22%的过程冲击。