Out of Control Planning

Problem Statement

  • Plan motions for non-holonomic systems whose dynamics are described by an ordinary differential equation of the form $$\dot{q} = f(q,u)$$
  • Compute the dynamically feasible and collision free motions for these systems using RRt and KPIECE planners
  • Learn about and implement a new planner called Reachability-Guided RRT (RG-RRT)

Results

The path for the three different planners KPIECE RRT and RGRRT are shown below:

Pendulum Path planners. Left image shows KPIECE planner, middle image RRT and right image shows RGRRT planner.
Car Path planners. Left image shows KPIECE planner, middle image RRT and right image shows RGRRT planner.

Benchmarking of the planners for both cases were perofrmed and the results obtained as shown below:

Pendulum

Computation Time
RRT KPIECE RGRRT Computation Time
Min Close to KPIECE Least Highest
Max Highest Close to RRT Lowest
Median Highest Least Close to RRT
1st Quartile Close to RGRRT Least Highest
3rd Quartile Highest Least Higher than RGRRT
Inter-Quartile Range Widest Smallest Higher than KPIECE
Solution Length
RRT KPIECE RGRRT Solution Length
Min Significantly high Highest Least
Max Significantly high Highest Least
Median Significantly high Highest Least
1st Quartile Significantly high Highest Least
3rd Quartile Significantly high Highest Least
Inter-Quartile Range Similar to KPIECE Highest Least
Tree Nodes
RRT KPIECE RGRRT Tree Nodes
Min Highest Significantly high Least
Max Highest Significantly high Least
Median Highest Significantly high Least
1st Quartile Highest Significantly high Least
3rd Quartile Highest Significantly high Least
Inter-Quartile Range Highest Similar to RGRRT Least
Success Rate
RRT KPIECE RGRRT Success Rate
Approximate solution 100% 100% 100%


Summarizing from the above table, we conclude that:

  • The median path length for RGRRT is the least.
  • The median number of tree nodes is very low for RGRRT.

Car

Computation Time
RRT KPIECE RGRRT Computation Time
Min Higher than RGRRT Highest Least
Max Close to KPIECE Least Highest
Median Close to KPIECE Highest Least
1st Quartile Close to KPIECE Highest Least
3rd Quartile Close to KPIECE Highest Least
Inter-Quartile Range Close to KPIECE Smallest Widest
Solution Length
RRT KPIECE RGRRT Solution Length
Min Highest Least Close to KPIECE
Max Highest Higher than RGRRT Least
Median Highest Least Very close to KPIECE
1st Quartile Highest Least Very close to KPIECE
3rd Quartile Highest Close to RGRRT Least
Inter-Quartile Range Highest Higher than RGRRT Least
Tree Nodes
RRT KPIECE RGRRT Tree Nodes
Min Highest Significantly high Least
Max Highest Significantly high Least
Median Highest Significantly high Least
1st Quartile Highest Significantly high Least
3rd Quartile Highest Significantly high Least
Inter-Quartile Range Highest Higher than RGRRT Least
Success Rate
RRT KPIECE RGRRT Success Rate
Approximate solution 100% 100% 100%


Summarizing from the above table, we conclude that:

  • The median path length for RGRRT and KPIECE is least and similar to each other. However path length varies more for KPIECE from one iteration to the other.
  • The median number of tree nodes is much much less for RGRRT.