Mobile Robot Path Planning Algorithm

In this paper, we propose a path planning algorithm for target mobile robots operating in unknown environments. The algorithm enables mobile robots to navigate around static obstacles and identify collision-free paths to reach their targets. Our designed approach provides multiple possible path options for robot movement from initial positions to target locations. We utilize grid-based mapping to represent unknown environments with static unknown obstacles, where the robot implements collision avoidance through remote sensing technology. During mission execution, the robot must plan optimal or feasible paths while minimizing costs related to time, energy consumption, and travel distance. Our path planning algorithm specifically accounts for obstacle avoidance while ensuring the robot safely reaches its target position.

To evaluate the performance of our proposed algorithm, we conducted simulations using MATLAB and MATLAB GUI. We implemented and tested the algorithm in two different three-dimensional coordinate system environments. Our simulation framework, developed in MATLAB, can be adapted to various planar objects and scenarios. The environment is segmented into discrete sections, allowing the robot to navigate from initial to target positions by following estimated trajectories mapped within the MATLAB GUI interface. The implementation includes key functions for grid mapping, path cost calculation, and real-time obstacle detection.

Through our algorithm, robots can safely navigate unknown environments and reach target positions, with simulation results demonstrating the effectiveness and reliability of our approach. The MATLAB-based simulation provides visualization of path planning processes and performance metrics analysis.