Optimal trajectory planning of industrial robot for improving positional accuracy Amruta Rout, Deepak BBVL, Bibhuti B. Biswal and Golak Bihari Mahanta Department of Industrial Design, National Institute of Technology, Rourkela, India Abstract Purpose – The purpose of this paper is to improve the positional accuracy, smoothness on motion and productivity of industrial robot through the proposed optimal joint trajectory planning method. Also a new improved algorithm, i.e. non-dominated sorting genetic algorithm-II (NSGA-II) with achievement scalarizing function (ASF) has been proposed to obtain better optimal results compared to previously used optimization methods. Design/methodology/approach – The end effector positional errors can be reduced by limiting the uncertainties of dynamic parameter variations like torque rate of joints. The jerk induced in robot joints due to acceleration variations are need to be minimized which otherwise induces vibrations in the manipulator that causes deviation in the encoders. But these lead to a vast increase in total travel time which affects the cost function of trajectory planning. Therefore, these three objectives need to be minimized individually so that an optimal trajectory path can be achieved with minimum positional error. Findings – The simulation results have been obtained by running the proposed hybrid NSGA-II with ASF in MATLAB R2017a software. The optimal time intervals have been used to calculate jerk, acceleration and torque values for consecutive points on the trajectory path. From the simulation and experimental results, it can be concluded that the optimization technique could be used effectively for the trajectory planning of six-axis industrial manipulator in the joint space on the basis of minimum time-jerk-torque rate criteria. Originality/value – In this paper, a new approach based on hybrid multi-objective optimization technique by combining NSGA-II with ASF has been applied to ﬁnd the minimal time-jerk- torque rate joint trajectory of a six-axis industrial robot for obtaining higher positional accuracy. The results obtained from the execution of algorithm have been validated through experimentation using Kawasaki RS06L industrial robot for a particular deﬁned path. Keywords Robot arm, Dynamic parameter, Kinematic Parameter, NSGA-II with ASF, Total travel time, Trajectory path Paper type Research paper 1. Introduction When the robots are used for industrial and medical applications high accuracy and repeatability is needed. The errors caused by the end-effector position and orientation are to be kept in speciﬁed limits for the safe operation and accurate results. The reason for the errors in robot trajectory planning are many which are actuator and controller dimensional tolerances, assembly and manufacturing errors and some measurement errors during manufacturing. So there is a need to analyze these uncertain factors for improving the positioning of the manipulator and should be ensured that the manipulators position and orientations are in speciﬁed tolerances. Initially, the requirement from the manufacturer is to complete the task in minimum possible time. Sahar et al. has proposed the trajectory planning for completing the task in minimum time which considers the dynamic constraints of the robot arm (Sahar et al., 1986). A control strategy is developed by Schoenwald et al. for minimum time trajectory generation considering joint arm actuator constraints of the robot and used efﬁcient ﬁnite element modelling. Often when only minimum time is considered as the objective for trajectory planning, it leads to variations in the kinematics and dynamics of the robot which affects the end-effector positioning(Schoenwald et al., 1991). Then for obtaining smooth motion, joint jerk along with total time has been considered as another objective for minimization. Huang et al. used global genetic approach for minimization of total jerks of the robot joints for trajectory planning subjected to dynamic and kinematic limits (Huang et al., 2006; Huang et al., 2007). Gasparetto and Zonotto presented a point to point trajectory planning algorithm for minimization of a weighted balance of total squared jerk and total travel time subjected to only kinematic constraints. The sequential quadratic programming (SQP) has been used to obtain the optimal solution for smooth trajectory planning (Gasparetto and Zanotto, 2008). Saravanan and Ramabalan presented the single objective function as weighted balance of actuator efforts and power, transfer time, joint jerk, acceleration and singularity avoidance for robot trajectory planning optimization. A comparative study of optimal The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/0143-991X.htm Industrial Robot: the international journal of robotics research and application © Emerald Publishing Limited [ISSN 0143-991X] [DOI 10.1108/IR-07-2019-0148] This research work is supported by Board of Research in Nuclear Sciences, Department of Atomic Energy, Government of India under project ID/ BRNS/34. Received 10 January 2019 Revised 30 August 2019 18 September 2019 Accepted 23 September 2019