Local Approaches

Basic Idea

1. Sensor data (e.g. lidar, sonar) is used to continuously detect obstacles as the robot moves.
2. Odometry data is used to obtain the robot’s current pose and velocity.
3. A set of possible solutions (candidates) are generated based on sensor and odometry data to steer the robot.
4. An objective function evaluates each possible solution.
5. The best (optimal) solution is selected and used to control the robot’s linear and angular velocities.
   Only a local region around the robot or a short time window is considered at a time for Obstacle Avoidance ⇒ locally optimal motion control.

Categories of Approaches