Reduction in Trajectory Error by Generating Smoother Trajectory for the Time-Efficient Navigation of Mobile Robot

Abstract

Robotics is intertwined with metrology, including aircraft component inspection, automotive processes, and part geometry optimization. Optimized trajectory planning is essential for reliable robotic arm operation and maintaining quality in inspections and geometric enhancements, as well as autonomous mobile robot navigation. Technically, a path planning is associated as an optimization problem that relies on various parameters such as length minimization problem, smooth trajectory planning, low time/space complexity, and computational load. While considering all these stated parameters, choosing an optimal path to reach the destination is the primary function of path planning techniques. This research paper is focused on the implementation of adaptive bidirectional A* (ABA*) algorithm along with new strategy of flexible controlling points technique (FCP) to reduce the trajectory error by generating smoother trajectory. With the increased number of sharp turns, the wheel skidding error is generated that reduce the reliability of the path planning techniques by increasing the pose estimation error. By conducting multiple trials, the proposed technique has been implemented, resulting in a 100% reduction in the number of collisions. Furthermore, the application of the new FCP technique eliminates all sharp turns, leading to a 38% decrease in time lag uncertainty compared to conventional approaches. The proposed technique improves autonomous navigation by selecting smoother trajectories.