Abstract
This paper presents the results of a motion planning algorithm that has been used in an intelligent citrus-picking robot consisting of a six-link manipulator. The real-time performance of a motion planning algorithm is urgently required by the picking robot. Within the artificial potential field (APF) method, the motion planning of the picking manipulator was basically solved. However, the real-time requirement of the picking robot had not been totally satisfied by APF because of some native defects, such as the large number of calculations used to map forces into torques by the Jacobian matrix, local minimum trap, and target not reachable problem, which greatly reduce motion planning efficiency and real-time performance of citrus-picking robots. To circumvent those problems, this paper proposed some novel methods that improved the mathematical models of APF and directly calculates the attractive torques in the joint space. By using the latter approach, the calculation time and the total joint error were separately reduced by 54.89% and 45.41% compared with APF. Finally, the novel algorithm is presented and demonstrated with some illustrative examples of the citrus picking robot, both offline during the design phase as well as online during a realistic picking test.
Highlights
Citrus fruit with rich nutritional value and good taste is loved by people all over the world
To improve the efficiency and success rate of the intelligent citrus-picking robot, the motion planning problem of a manipulator—which was the core component of the citrus-picking robot—was studied in-depth, and a novel improved artificial potential field (APF) algorithm was proposed by improving the models of potential fields and forces of APF and designing some optimization strategies, which greatly reduced the calculation amount of its application in the process of motion planning of a manipulator
The ETS method is used to model the kinematics of the EC63M manipulator, and the Jacobian matrix of each point on the manipulator relative to the base coordinate frame can be obtained by this model
Summary
Citrus fruit with rich nutritional value and good taste is loved by people all over the world. The above studies have effectively avoided the LMT, the application object is a mobile vehicle rather than a manipulator, so it cannot be directly applied to a picking robot for real-time motion planning. [30] combined RRT with APF and proposed a velocity potential field method for obstacle avoidance motion planning of manipulators based on virtual target points. It could effectively avoid falling into LMT, but the path planning for a planar 3-DOF manipulator took at least 4.15 s. W. et al [31] improved the attractive potential field calculation formula of APF by introducing a Cartesian space boundary, but it took mor than 5 s for path planning of self-designed 9-DOF manipulator to get very ocfl1o8se to th target configuration. Ur,max, kr, kr2 deformation control factors of the anti-S type Sigmoid function
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