Mobile robots are autonomous machines that can move around in their environment to perform tasks without direct human control. They can vary from simple machines, like vacuum cleaning robots, to complex systems used in warehouses or for delivery services. These robots rely on various technologies to navigate their surroundings, which can be challenging if the environment is dynamic—meaning it changes in real-time due to obstacles, people, or other variables.
To navigate dynamically, mobile robots use a combination of sensors and algorithms. Common sensors include cameras, LiDAR (Light Detection and Ranging), ultrasonic sensors, and GPS. For instance, LiDAR helps the robot measure distances to objects around it by sending out laser beams and measuring how long it takes for them to bounce back. This data is crucial for creating a 3D map of the robot's surroundings. Additionally, cameras enable robots to recognize objects and features, such as doorways or furniture, enhancing their ability to move safely and efficiently.
Once equipped with sensors, robots employ algorithms for path planning and obstacle avoidance. Path planning algorithms, such as A* or Dijkstra's algorithm, help the robot determine the best route to its destination while considering current obstacles. Simultaneously, real-time algorithms like Dynamic Window Approach help the robot make immediate decisions when new obstacles are detected. These systems work in tandem, allowing the robot not only to navigate predefined routes but also to adapt its path in response to unexpected changes, ensuring safe and effective operation in bustling environments.