An analytic approach to moving obstacle avoidance using an artificial potential field

This paper proposes a unified method for moving obstacle avoidance of a robot. The method incorporates the artificial potential field (APF) concept into view-time based motion planning where the driving force is generated at every interval of the view-time. The view-time is defined as the time set from one sampling time instant to the next. The velocity and acceleration of the moving obstacle is assumed to be monitored or priorly known at each sampling time. At each sampling time, an accessible region that will be swept by the obstacle in the next view-time is predicted from the velocity, acceleration, and dynamic constraints of the obstacle. Then, an APF which exerts repulsive force on the robot is constructed around the accessible region. During the view-time, the force induced by the artificial potential field drives the robot away from the accessible obstacle trajectories in real-time. The dynamic constraints of the robot are also considered. Application of the described procedure at each successive sampling time from the initial to final location yields the collision-free trajectory for moving obstacle avoidance.

Authors

• Yun Seok Nam
• Bum Hee Lee
• Nak Yong Ko

Keywords

• Robots
• Sampling methods
• Acceleration
• Motion planning
• Monitoring
• Obstacle Avoidance
• Artificial Potential Field
• Moving Obstacle Avoidance
• Sampling Time
• Path Planning
• Accessible Regions
• Collision-free Trajectory
• Order Polynomial
• Cartesian Space
• Robot Motion
• 2-dimensional Space
• Smoothness Constraint
• Polar Coordinate System
• Velocity Of The Robot