Obstacle Free Robot Motion Planning and Intelligent Maneuvering Controller

Abstract

Autonomously controlled wheeled mobile robots (WMRs) are often instructed to navigate on a previously planned path through predefined control points within a clumsy obstacle-prone environment. In most path planning techniques, the planned path does not pass through all intermediate control points. Although, if the path passes through the intermediate control points in some cases, the overall path is constructed by many segments with the fulfillment of continuity criteria. Due to multiple segments, the existing path planning and control methods may sometimes fail to restore the WMR to its original planned path after negotiating obstacles. Considering the afore-mentioned drawback, a single segmented polynomial function-based motion planning cum path-following scheme suitable in confined and restricted places with the capability of negotiating unexpected obstacles is proposed in this article. The polynomial function is formulated based on the least square method encap-sulating all the predefined control points to the closest range. The proposed function is used as the position output function for the input-output feedback linearization controller (FBC) to maneuver the WMR through the planned path in a path-following paradigm. Further, considering a static and dynamic obstacles-prone working envelope, a fuzzy logic controller (FLC) is embedded with the FBC to inculcate intelligent behavior. Due to a single segment-based polynomial path, the intelligent controller ensures reinstating the WMR on the original path after avoiding obstacles. Finally, the effectiveness of the unique robot motion planning framework in avoiding collisions is illustrated in a simulated environment using robot parameters, and the relevance of the current research work is established over the piece-wise cubic spline-based path planning framework.