Obstacle Avoidance and Path Planning of a Wheeled Mobile Robot Using Hybrid Algorithm

In the mobile robot workplace, path planning problem is crucial. Robotic systems employ intelligence algorithms to plan robot's from one point another. This paper proposes fastest and optimal of wheeled with collision avoidance find route during navigation start target point. It done using a modern meta-heuristic hybrid algorithm called IPSOGWO by combining Improved Particle Swarm Optimization (IPSO) Grey Wolf Optimizer (GWO). The principal idea based on boosting ability exploit in PSO exploration GWO better-automated alignment between local global search capabilities towards targeted, optimized solution. proposed tackles two objectives: protection length path. During, Simulation tests are compared individual results PSO, IPSO, concepts about minimum path, execution time, number iterations required achieve best route. work's effective was evaluated MATLAB environment. simulation indicated that developed reduced average computation less than (1%, 1.7%), 1.9%), IPSO (0.05%, 0.4%), respectively. Furthermore, superiority proved through comparisons other famous different static environments.