Extended Potential Field Method

1
Extended Potential Field Method

• Adam A. Gonthier
• MEAM 620 Final Project
• 3/19/2006

2
Potential Field Approach

• Can use continuous configuration space
• Therefore, avoids complexities of discrete
  planning
• Field is modeled by potential functions

• Benefits
• Local method
• Does not require global map
• No prior knowledge of obstacles required
• Drawbacks
• Get caught in local minima
• Does not find optimal path
• Obstacles, robot modeled as points in real
  world, they are not points

3
Potential Field Approach

• Goal is modeled as attractive force
• Obstacles modeled as repulsive forces
• Robot modeled as point
• Robot follows gradient of force field, stopping
  at goal point

2-D Symmetric Gaussian Obstacle
Parabolic Goal Well
Total Potential Field
4
Potential Field Algorithm

• Very simple algorithm
• Start at initial point
• Find path opposite to gradient
• Set new point at distance d along path from old
  point
• Repeat until goal point is reached

-Prof. John Spletzer Lehigh University
5
Potential Field Extension
M. Khatib and R. Chatila

• In addition to the goal and obstacle potentials,
  include rotation and task potentials
• Rotation Potential
• A potential function for the robots orientation
  relative to the goal is considered, thus forcing
  the robot along a straighter path
• Task Potential
• Filter out obstacles that should not influence
  the robots motion the obstacles that are not in
  the robots path.
• These additions should help create a superior
  path for the robot
• The rotation field helps avoid overturning from
  an obstacle
• The task field helps avoid unnecessary turning.

6
Goal and References

• Goal
• To produce a Matlab implementation of the
  extended potential fields method for several
  configurations

• References
• Prof. John Spletzer
• http//www.cse.lehigh.edu/7Espletzer/cse397_Fall0
  5/lec014_MotionPlanning.pdf
• H. Choset et al (2005). Principles of Robot
  Motion Theory, Algorithms and Implementations.
  Cambridge, MA. MIT Press
• M. Khatib and R. Chatila. An extended potential
  field approach for mobile robot sensor-based
  motions. In Proc. Int. Conf. on Intelligent
  Autonomous Systems (IAS'4), 1995.
• R. W. Beard and T.W. McLain, Motion Planning
  Using Potential Fields, January 2003