Differential Robot Projects
Last updated
Last updated
The Differential Robot Project is a hands-on application of the Acrome Motion Kit, designed to introduce students, researchers, and robotics enthusiasts to differential drive systems, motion control, and autonomous navigation.
With this kit, users can build and program a differential-drive mobile robot, enabling real-time motion planning, obstacle avoidance, and sensor integration. It serves as an ideal platform for robotics education, AI research, and industrial automation prototyping.
A differential drive robot is a type of wheeled robot that moves by controlling the speed of two independent motors. This movement mechanism allows for:
Straight Motion – Both wheels move at the same speed. Turning – One wheel moves faster than the other. Rotation in Place – The wheels rotate in opposite directions.
This simple yet powerful design is commonly used in autonomous robots, self-driving vehicles, industrial AGVs (Automated Guided Vehicles), and AI-based navigation systems.
The Differential Drive Robot supports multiple control and programming methods, making it adaptable for users with different skill levels:
Ideal for beginners and classroom learning.
Allows users to control motors, read sensor data, and implement logic without coding.
Example Blockly command: Move Forward at 50% Speed.
Offers detailed control over motor speed, sensor feedback, and real-time decision-making.
Supports PID control and adaptive movement strategies.
Example Python script:
Enables wireless remote control through a smartphone or tablet.
Uses Bluetooth or Wi-Fi for connectivity.
Differential drive robots are used in a variety of real-world applications, including:
Autonomous Vehicles – Found in self-driving cars and delivery robots. Industrial Automation – Used in factories, warehouses, and AGVs. AI & Machine Learning – Research in reinforcement learning and path optimization. STEM Education & Competitions – Helps students develop robotics and programming skills.
Braitenberg Robot: A reactive robot that simulates behavior based on sensory input, demonstrating simple bio-inspired logic.
Line-Follower Robot: Uses infrared sensors to detect and follow lines autonomously, ideal for teaching basic PID control.
Object Tracking Robot: Employs vision or distance sensors to follow or avoid dynamic targets.
Teleoperation Robot: Remotely controlled via mobile app or interface, perfect for exploring wireless control and safety limits.
Obstacle Avoidance Robot: Utilizes a pan-tilt ultrasonic sensor system to actively scan the environment and avoid obstacles in real time, offering a hands-on introduction to autonomous navigation and sensor fusion.