LiDAR Driven Maze Robot
CompletedThe LiDAR Driven Maze Bot project was an ambitious initiative led by the Texas A&M University Robotics team. This project aimed to develop an advanced robotic system capable of autonomously navigating complex mazes by integrating state-of-the-art LiDAR technology and sophisticated control algorithms. The challenge was to optimize both the mechanical and software aspects while maintaining cost efficiency.
Hardware Enhancements
At the heart of the robot’s movement system was a carefully selected combination of high-performance motors and precision encoders. To ensure reliable navigation, we incorporated high-torque 750Kv motors, which provided enhanced rotational force essential for maneuverability. The addition of 8192 CPR encoders allowed for precise position tracking, ensuring that the bot could accurately measure and adjust its movements.
For motor control, we implemented the ODrive 3.6 motor controller, which enabled dynamic velocity profiling, ensuring smooth and efficient motion. Stability was further reinforced with a DC voltage step-down converter, guaranteeing a steady power supply to critical components. To enhance communication and connectivity, the Jetson WiFi Module was integrated, facilitating seamless data transfer between the onboard computing system and external monitoring interfaces.
Mechanical Design and Fabrication
The mechanical design of the robot was engineered to balance performance and reliability. We designed a 6:1 gear ratio, ensuring an optimal balance between torque and speed, crucial for precise navigation through the maze. The entire base of the robot was CAD-modeled, integrating motor mounts that streamlined assembly and improved structural integrity.
Fabrication involved a combination of laser-cut precision components for high accuracy and 3D-printed custom parts, allowing for flexible modifications and design iterations. The frame was meticulously designed to house all electrical components securely, ensuring durability and ease of maintenance.
Software Development
On the software side, the project leveraged modern robotics frameworks and advanced algorithms to achieve seamless autonomous navigation. ROS 2 Humble served as the core framework for message passing and visualization, ensuring real-time data communication between sensors, controllers, and decision-making algorithms.
Path planning was enhanced using Fast-Marching Trees, an efficient algorithm for generating feasible navigation paths within complex environments. To ensure smooth trajectory execution, Bezier Curves were employed for generating continuous, obstacle-free motion paths. Additionally, TOPPRA (Time-Optimal Path Parameterization) was integrated to fine-tune movement speed, ensuring optimal performance in dynamic conditions.
Advanced Technologies
The robot’s perception system relied on the RPLidar A1, a cost-effective yet powerful LiDAR sensor used for environment mapping. Running on a Jetson Nano with Linux 18.04, the system was capable of real-time data analysis and autonomous decision-making. The integration of these components allowed the robot to dynamically adapt to its environment, making intelligent navigation decisions without human intervention.
Future Enhancements
While the project successfully achieved its goal of autonomous maze navigation, several improvements are planned for future iterations. Enhancements in control software will refine navigation precision, while a deeper LiDAR integration will improve environmental perception. Advanced localization techniques, including multi-sensor fusion, will further increase accuracy. Ultimately, the goal is to achieve fully autonomous navigation, enabling the robot to operate seamlessly in even more complex and dynamic environments.
The LiDAR Driven Maze Bot is a testament to the potential of robotics in real-world navigation challenges. With ongoing improvements, it stands to become an even more capable autonomous system, pushing the boundaries of robotic intelligence and control.