Reliable autonomous navigation of mobile robot in unconstrained environment

Path optimization is one of the crucial problems in unmanned ground vehicles. It is associated with various concerns such as smooth trajectory, collision free planning, less time/space complexity, etc. Rapid Exploring Random Tree (RRT) provides an effective path planning however, it introduces sharp turns leading to increased travel time. Further, the mobile robot needs to align its heading angle ($\theta$) with the trajectory angle ($\beta$) else it may collide with the obstacles. Hence in this work, Improved RRT Theta algorithm is proposed that is an amalgamation of improved RRT with modified B Spline curve technique. The heading angle is aligned with the trajectory angle for collision free navigation of mobile robot and a modified B Spline method adds the new control points in the trajectory to reduce the number of sharp turns. The proposed technique is tested for different simulation based environmental conditions. The results reveal that the proposed technique proves to be an efficient path planning technique with collision free smooth movement, reduced time lag and path length as compared to the conventional RRT technique. The proposed technique may be quite helpful in autonomous navigation, trajectory tracking, path planning etc.