Performance Analysis of Autonomous Mobile Robot Navigation
Implementation Plan:
—————————-
Step 1: Initially, we construct an autonomous mobile robot navigation environment with defined start point, goal point, and obstacle maps.
Step 2: Then, we collect data by generating simulation-based path planning data using standard grid maps (Narrow, Cluttered, Maze).
Step 3: Next, we preprocess the collected map data by converting maps into obstacle-free configuration space and defining collision-checking constraints.
Step 4: Next, we implement hybrid path planning Hybrid-RRT* algorithm based on the collected environment data.
Step 5: Next, we analyze uniform and non-uniform sampling in a proposed Hybrid-RRT* using a random switching parameter (α = 0.5)
Step 6: Next, we detect generated paths, trees, and convergence behavior based on collected data.
Step 7: Finally, we evaluate and plot performance metrics for the following
7.1: Number of iterations vs. Path Length
7.2: Number of iterations vs. Planning Time
7.3: Number of iterations vs. Convergence Rate
7.4: Number of iterations vs. Success Rate (%)
Software Requirements:
—————————–
1. Development Tool: MATLAB R2023a or above
2. Operating System: Windows-10 (64-bit) or above
Note:
——
1) If the proposed plan does not fully align with your requirements, please provide all necessary details—including steps, parameters, models, and expected outcomes—in advance.
2) Kindly ensure that any missing configurations or specifications are clearly outlined in the plan before confirming.
3) If there’s no built-in solution for what the project needs, we can always turn to reference models, customize our own, different math models or write the code ourselves to fulfil the process.
4) If the plan satisfies your requirement, Please confirm with us.
5) Project based on Simulation only.
