Optimizing Redundant Robot Kinematics and Motion Planning via Advanced D-H Analysis and Enhanced Artificial Potential Fields
Abstract
:1. Introduction
- A method for the optimal solution of robot inverse kinematics is proposed. Specifically, the DH parameter method is used to solve the eight sets of joint vectors of the redundant manipulator. On this basis, we design an objective function that takes into account the accuracy of the inverse solution of the manipulator and the smoothness of the manipulator’s motion, thereby obtaining the optimal solution of the redundant manipulator.
- An enhanced path planning algorithm utilizing an improved artificial potential field method is introduced. This advancement addresses the issues associated with discontinuous changes in gravitational potential at zero points and the excessive gravitational potential over long distances, which are prevalent in traditional artificial potential field approaches for manipulator path planning.
- The operational principles and underlying logic of the rapidly exploring random tree (RRT) algorithm are thoroughly examined.
2. Kinematics Analysis of Redundant Manipulator
2.1. Forward Kinematics Modeling
2.2. Inverse Kinematics Analysis
2.3. Simulation and Verification
3. Motion Planning Algorithm for Manipulator
3.1. Artificial Potential Field
3.2. Rapidly Exploring Random Tree
Algorithm 1 Rapidly Exploring Random Tree Algorithm Pseudo Code | |
Input: | qS, qG, λ |
Output: | T |
1: | T init = qS |
2: | for k = 1 : K do |
3: | qrand ← GetRandomNode() |
4: | q_closest ← NearNeighbor(T, qrand) |
5: | qnew ← SteerNode (qrand, qclosed, λ) |
6: | if CollosionFree() then |
7: | T.add_vertex(qnew) |
8: | end if |
9: | if GettheGoal then |
10: | return T |
11: | end if |
12: | end for |
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Link i | (Rad) | (mm) | (mm) | (Rad) |
---|---|---|---|---|
1 | 0.0 | −π/2 | ||
2 | 0.0 | 0.0 | −π/2 | |
3 | 0.0 | −π/2 | ||
4 | 0.0 | 0.0 | −π/2 | |
5 | 0.0 | −π/2 | ||
6 | 0.0 | 0.0 | −π/2 | |
7 | 0.0 | 0 |
(Rad) | Initial Value (Rad) | CalculatedValue (Rad) | SimulationValue (Rad) | Error (Rad) |
---|---|---|---|---|
0.0 | 0.391410 | 0.391297 | 0.00156 | |
0.0 | −0.676384 | −0.677152 | 0.00768 | |
0.0 | −0.376217 | −0.375910 | 0.00307 | |
0.0 | 0.543211 | 0.543113 | 0.00010 | |
0.0 | 1.052834 | 1.051979 | 0.00085 | |
0.0 | 0.454125 | 0.454538 | 0.00042 | |
0.0 | 0.123246 | 0.122632 | 0.00058 |
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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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Zhang, X.; Chen, L.; Dong, W.; Li, C. Optimizing Redundant Robot Kinematics and Motion Planning via Advanced D-H Analysis and Enhanced Artificial Potential Fields. Electronics 2024, 13, 3304. https://doi.org/10.3390/electronics13163304
Zhang X, Chen L, Dong W, Li C. Optimizing Redundant Robot Kinematics and Motion Planning via Advanced D-H Analysis and Enhanced Artificial Potential Fields. Electronics. 2024; 13(16):3304. https://doi.org/10.3390/electronics13163304
Chicago/Turabian StyleZhang, Xuanming, Lei Chen, Weian Dong, and Chunxu Li. 2024. "Optimizing Redundant Robot Kinematics and Motion Planning via Advanced D-H Analysis and Enhanced Artificial Potential Fields" Electronics 13, no. 16: 3304. https://doi.org/10.3390/electronics13163304