We built a robotic vehicle, named Alex, equipped with search and rescue functionalities to navigate and map a simulated disaster environment.
"Alex to the Rescue" focuses on leveraging recent advancements in robotics to aid in disaster response scenarios. Students will develop a robotic vehicle capable of navigating through simulated obstructions and mapping the environment in real-time. The project aims to highlight the critical role of technology in enhancing the efficiency and effectiveness of rescue operations within the crucial 72-hour golden period following a disaster.
- Environment Mapping: Alex will be remotely controlled to navigate and map the simulated environment, with the mapping data relayed back to the operator.
- Obstacle Identification: Incorporating sensors, Alex will detect and identify objects of interest, such as simulated survivors, within the environment.
- Evaluation Criteria: The project will be assessed based on the time taken to complete the mapping, obstacle avoidance capabilities, the completeness and accuracy of the environment map, and the innovative functionalities introduced to enhance Alex's capabilities.
- Lidar: Utilized for mapping the environment and obstacle detection.
- SLAM Algorithm: Employs Simultaneous Localization and Mapping to navigate and map the environment accurately.
- Ultrasonic Sensors: For obstacle detection and avoidance.
- Infrared Sensors: Used to identify specific objects within the environment.
- Raspberry Pi: Acts as the master control program (MCP) to process commands and control the vehicle.
- Arduino: Receives signals from the Raspberry Pi to control the robotic vehicle's movements.