Abstract
Mobile robots have various applications in agriculture, autonomous cars, industrial automation, planetary exploration, security, and surveillance. The generation of the optimal smooth path is a significant aspect of mobile robotics. An optimal path for a mobile robot is measured by various factors such as path length, path smoothness, collision-free curve, execution time, and the total number of turns. However, most of the planners generate a non-smooth less optimal and linear piecewise path. Post processing smoothing is applied at the cost of increase in path length. Moreover, current research on post-processing path smoothing techniques does not address the issues of post smoothness collision and performance efficiency. This paper presents a path smoothing approach based on clamped cubic B-Spline to resolve the aforementioned issues. The proposed approach has introduced an economical point insertion scheme with automated knot vector generation while eliminating post smoothness collisions with obstacles. It generates C2 continuous path without any stitching point and passes more closely to the originally planned path. Experiments and comparison with previous approaches have shown that the proposed approach generates better results with reduced path length, and execution time. The test cases used for experiments include a simple structure environment, complex un-structured environment, an environment full of random cluttered narrow obstacles, and a case study of an indoor narrow passage.
Highlights
Optimal path planning for mobile robots is an important aspect of motion planning with various applications in industrial robots [1], planetary exploration robots [2,3,4], medical robots [5,6], humanoid robots [7], driver-less cars [3], cleaning robots [8], and Un-manned Aerial Vehicle (UAV)
This paper presents a path smoothing approach based on clamped cubic B-Spline that generates a shorter path, and performs automated collision avoidance for a post smoothing path
Collision-free smoothness: It is the most crucial metric as a smooth path obtained in minimal computational time with required continuity and short length will be of no use if it is not free from collision
Summary
Optimal path planning for mobile robots is an important aspect of motion planning with various applications in industrial robots [1], planetary exploration robots [2,3,4], medical robots [5,6], humanoid robots [7], driver-less cars [3], cleaning robots [8], and Un-manned Aerial Vehicle (UAV). Smooth path generation has applications in mobile robotics, and in medical ultra-precision motion systems such as hip and knee implants for smoothness and the accuracy of movement trajectory [16]. Path planners such as Memory Efficient A* (MEA*), Rapidly exploring Random Tree. These approaches result in post smoothness collision in a complex environment, which leads to the failure of the robot’s movement They generate longer paths with deviation from originally planned paths and they use a large number of control points.
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