An Improved Spherical Vector and Truncated Mean Stabilization Based Bat Algorithm for UAV Path Planning

Unmanned aerial vehicles have a wide range of applications. An intelligent optimization algorithm based on the traditional bat (BA) is investigated in this paper for UAV flight path planning static complex environment. The primary goal work to develop safer while considering feasibility and requirements safe operation. This research proposes an improved spherical coordinate truncated average stable strategy-based (TMS-SBA). uses UAV’s motion space encode operator, by substituting new worst old one after each iteration increase population diversity, can converge quickly environment maintaining In addition, smoothly generated using B-spline curves make planned suitable UAV. MATLAB simulation experiments show that, compared with other swarm algorithms, TMS-SBA successfully generate feasible effective optimal solutions environments plan shorter, safer, more accessible paths