Autonomous Robot Navigation: Python Coding in Webots

Develop Python Code for Autonomous Robot Navigation and Mapping in Webots Project Overview: I am working on a personal project in Webots, where a robot must autonomously navigate an arena, avoid obstacles, and generate an Occupancy Grid Map of the environment. The project should implement efficient navigation, mapping, and obstacle avoidance strategies using Python. The final solution will be tested in Webots R2023b (or earlier versions if specified). Key Requirements: Navigation and Exploration: Implement goal-seeking navigation using a closed-loop controller. Include acceleration and deceleration based on proximity to the start, goal, or obstacles. Implement obstacle avoidance using a PID-based wall-following strategy. Use the Bug1 algorithm for complex obstacle avoidance. Ensure reliable navigation for at least one arena ([login to view URL] or [login to view URL]). Occupancy Grid Mapping: Integrate the provided OccupancyGrid class to build a map of the environment. Implement the log-odds inverse sensor model for the grid. Update occupancy probabilities dynamically based on sensor input. Sensors and Obstacle Detection: Utilize the PioneerSimpleProxSensors class to detect walls and obstacles. Integrate touch (bumper) sensors for fail-safe obstacle detection. Report and Demonstration: Provide a 500–1000 word report explaining: Navigation strategies. Challenges faced and resolutions. Include screenshots of generated maps. Deliver a video demonstrating the robot's functionality in the arena. Resources Provided: [login to view URL], [login to view URL], and [login to view URL] classes for navigation and sensing. Occupancy Grid template for dynamic mapping. Detailed tutorial and pseudocode for navigation and obstacle avoidance (Bug1 algorithm, PID wall-following, etc.). Two arena files ([login to view URL] and [login to view URL]) for testing. Python Code Tasks: Complete the OccupancyGrid class to implement the log-odds sensor model. Develop a robust navigation controller: Closed-loop goal-seeking. Acceleration and deceleration. Wall-following with PID control. Obstacle avoidance with Bug1 algorithm. Integrate touch sensors for obstacle detection. Test and ensure the solution runs smoothly in Webots. Deliverables: Completed Python scripts for: Navigation ([login to view URL]). Sensing ([login to view URL]). Pose management ([login to view URL]). Controller ([login to view URL]). Full zipped Webots project directory with a functional controller. A concise report in PDF format. A video demonstrating the robot's exploration and mapping. Deadline: 7 days from project start date. Evaluation Criteria: Completeness of map (coverage and accuracy). Navigation sophistication (smooth goal-seeking and obstacle avoidance). Clean and well-commented code. Quality of report and demonstration video. Additional Information: The project builds on concepts: Goal-seeking using a closed-loop controller. PID-based wall-following. Bug1 algorithm for navigating around obstacles.