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Abstract
In recent years, a large number of manipulator robots have been deployed to replace or assist humans in many repetitive and dangerous tasks. Yet, these robots have complex mechanisms, resulting in their non-linearity of kinematics and dynamics as well as intensive computations. Therefore, relying on soft computing techniques are a common and alternative key to model and control these systems. In particular, fuzzy logic approaches have proven to be simple, efficient, and superior to relevant well-known methods and have sparked greater interest in robotic applications. To help researchers meet their needs easily and quickly in finding relevant research works on fuzzy-based solutions, this article adapted to provide an in-depth review of the currently updated fuzzy logic approaches for collision-free path planning of serial manipulator robots operating in complex and cluttered workspaces. In addition to a comprehensive description of fuzzy hybridization with other artificial intelligence techniques description. Further, this article attempts to present the main solutions with a summary and visualization of all basic approaches that path-planning problems may subtend in the decision-making process. Finally, the paper suggests some potential challenges and explores research issues for future work.
AI/ML
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