Lecture 6
24-354 General Robotics
Fall-05. Prof. Howie Choset

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• Inspiration for interest in robotics
  • Wish to augment the capabilities of a human
  • Wish to avoid having a human do dangerous or undesireable work
  • Wish to benefit human life. (Biomedical applications)
  • They are just plain fun.
  
  
• Motion Planning
  
• Motion planning is concerned with how a robot traces a trajectory (velocities/accelerations); Path planning is only concerned with the generation of a path to follow.
• Applications for path planning include:
  • Navigation
  • Mapping
  • Coverage
  
  
• An obstacle is convex if all points on a line connecting any two points in the object belong to the object.
• A path planner is complete if it returns a path in a finite time or returns that no path exists in a finite time.
• The BUG 2 Algorithm
  • Head toward the goal in a straight line.
  • If you hit an obstacle, circumvent it until you reach the line connecting the start and goal, called the mline.
  • If the leave point is closer to the hit point continue toward the goal in a straight line
    • Else, continue around the obstacle
  • If you return to the same hit point without defining a leave point, then you have gone completely around the obstacle and the goal is not reachable (return failure.)
    

    BUG2 with LEFT direction		BUG2 with RIGHT direction

• Motion Planning: Potential Functions
  • Charge-analogy
    
  • Distance Function (L1 and L2)
    
    
    
    D(x) = min d_i(x)
  • Attractive/Repulsive Potential Functions
    • Attractive: Distance to goal
    • Repulsive: Distance to obstacles