Optimal Trajectory Planning of Grinding Robot Based on Improved Whale Optimization Algorithm

Wang, Ting; Xin, Zhijie; Miao, Hongxia; Zhang, Huang; Zhen-ya, Chen; Du, Yunfei

doi:10.1155/2020/3424313

Cited by 25 publications

(17 citation statements)

References 23 publications

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“…An improved ant colony optimization algorithm is proposed to obtain the optimal path planning satisfying the moving target. The results prove the accuracy and efficiency of the proposed method in realizing the optimal path and trajectory [2].…”

Section: Introductionsupporting

confidence: 52%

Global Optimal Time Trajectory Planning of Construction Machinery Robot Considering Ant Colony Algorithm

2022

KME

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In the practical application of industrial robots, efficiency and quality are important indicators to evaluate the performance of robots. In the continuous path path planning, reasonable path planning and time optimization are crucial to the efficient, accurate and reliable operation of industrial robots. In this paper, on the basis of consulting and analyzing the research of domestic and foreign experts and scholars on trajectory planning, the ant colony algorithm(ACA) is proposed and applied to the optimal time(OT) trajectory global planning of construction machinery robot(CMR) for research and analysis. the ACA is used to optimize the RT of the joints. The planning goal of the optimal RT of each joint of the robot is achieved.

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Section: Introductionsupporting

confidence: 52%

Global Optimal Time Trajectory Planning of Construction Machinery Robot Considering Ant Colony Algorithm

2022

KME

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“…T. e control vertex vector can be obtained by the above formula and then the motion trajectory of each joint and the expression of the speed, acceleration, and jerk of each joint can be obtained according to formulas (17) and (22).…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

“…In the research of trajectory optimization [15,16], researchers mainly focus on using various algorithms to optimize performance indicators such as time, energy consumption, and flatness [17][18][19]. Most of them use genetic algorithm (GA), ant colony algorithm (ACO), particle swarm algorithm (PSO) [20][21][22], etc., among intelligent algorithms in the group.…”

Section: Introductionmentioning

confidence: 99%

Error Compensation Trajectory Planning Method of Brake Disc Shaft Hole Assembly considering Robot Accumulated Error

Liu

2022

Mathematical Problems in Engineering

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Aiming at the problem of alignment deviation between shaft and hole caused by accumulated error in the assembly process of brake disc shaft hole, a trajectory planning method for compensating accumulated error is proposed. First, the path before the error is planned, and then the second compensation path is planned between the error position and the actual target point, so as to realize the accurate assembly of the brake disc. In this paper, the IRB 1410 robot is taken as the research object, and its kinematic model is established by using the improved D-H parameter method. The joint space quintic B-spline interpolation method was used to carry out trajectory planning, and the improved particle swarm optimization algorithm was introduced to solve the optimization. The optimal time and smooth trajectory were expected to be obtained. Then, using MATLAB software to simulate, compared with the nonoptimized trajectory, not only is the trajectory running time reduced from 8.6 s to 6.7 s but also the maximum joint change angle of each joint is reduced, which proves that the algorithm has optimization effect on trajectory running time and stability. Finally, the accuracy verification experiment of the algorithm is carried out, and the error between simulation and experiment is less than 6%, which shows the effectiveness of the method. This research provides a theoretical basis for improving the responsiveness and stability of brake disc assembly.

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“…Guo et al [21] combined an improved whale optimization algorithm with social learning and wavelet mutation strategies to estimate the water resources demand. Wang et al [22] proposed an improved whale optimization algorithm (IWOA) and evaluated its effectiveness to realize the optimal path planning of the grinding robot. In this regard, Liu et al [23] proposed a hybrid WOA combined with differential evolution and Levy flight (WOA-LFDE) to solve job shop scheduling problems.…”

Section: Iintroductionmentioning

confidence: 99%

Serial Manipulator Time-Jerk Optimal Trajectory Planning Based on Hybrid IWOA-PSO Algorithm

2022

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Loading and unloading operations are widely employed in industrial robots and CNC machine tools. In the present study, an effective algorithm is established for optimum time-jerk path planning and reducing the vibration of the serial manipulator, and enhancing the robot efficiency. To this end, the manipulator's trajectory is constructed using quintic B-spline interpolation in the joint space and the optimal objective function is constructed in terms of time and mean jerk. A hybrid improved whale optimization and particle swarm optimization (IWOA-PSO) method is proposed to optimize the objective function. First, WOA is improved by employing adaptive weight and threshold to balance exploration and exploitation of the WOA to prevent falling into the local optimum solution. Then, PSO method and IWOA techniques are combined to enhance the convergence speed of the IWOA. Applying different algorithms to 23 benchmark functions demonstrate superiority of the proposed algorithm to state-of-the-art algorithms. A 6-DOF serial industrial manipulator integrated in CNC machine was taken as a case study and the joint positions are considered the IWOA-PSO inputs. All calculations are performed in the MATLAB 2018b environment. The obtained results demonstrate that the proposed IWOA-PSO can effectively reduce the jerk of the robot while improving its work efficiency.

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Optimal Trajectory Planning of Grinding Robot Based on Improved Whale Optimization Algorithm

Cited by 25 publications

References 23 publications

Global Optimal Time Trajectory Planning of Construction Machinery Robot Considering Ant Colony Algorithm

Global Optimal Time Trajectory Planning of Construction Machinery Robot Considering Ant Colony Algorithm

Error Compensation Trajectory Planning Method of Brake Disc Shaft Hole Assembly considering Robot Accumulated Error

Serial Manipulator Time-Jerk Optimal Trajectory Planning Based on Hybrid IWOA-PSO Algorithm

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