rrtPlanner

Implementation of RRT Motion Planning

  • This is a project I completed in the summer of 2018, under Karen and Sipu’s help, in Johns Hopkins University.
  • This can be found on my github page.
  • This is an implementation of Rapid-exploring Random Tree Algorithm on ROS, in 2D plane and the robot, obstacles and world are all in a shape of ellipsoid. The main language is C++.

Motion Planning with RRT

The procedure of RRT planner is described below:

  • Initialize: build a RRT tree whose root is the start point (in a n-dimension space) of the motion. Every node in the tree represents a “valid” point in the C-Space, which means under that position the robot is not in collision.

  • Explore the C-Space and grow the tree: (loop)

    • Generate a random pose of the ellipsoid robot ()
    • Traverse all the node in the tree and find a , which is nearest to the
    • Generate a new point which is between and and is a metric away from
    • IF ( is valid ) THEN { add to the tree}. Once the goal is achieved or the search time is more than the set upper limit, the search should be terminated.
  • Find the trajectory from the generated tree, if the goal is successfully achieved. Dijkstra Algorithm can be used.

  • Smooth the trajectory.

RRT implementation in 2D with a point

The Structure of My ROS Package

msg

  • ellipsoid.msg: ellipsoid semi-axes length, central point ordinates value, angle
  • world.msg: describe the arena, obstacles and robot with ellipsoid message
  • position.msg: (x, y, 𝜙) value describing the ellipsoid pose
  • point.msg: (x, y) value describing the 2D point
  • trajectory.msg: an array of (x, y) describing the points on the trajectory
  • pointsArrary.msg: an array of (x, y) on the boundary of ellipsoid generated by the server
  • node.msg: the x, y values of the valid searched node, father value represents the nearest node ID
  • rrtGraph.msg: array of node

srv

  • collision_detect.srv: return whether the state is in collision according to the world msg information and current robot position msg
  • ellipsoid_points.srv: return a vector of point msg according to the ellipsoid msg and step

include/rrt_implement

  • rrt.h: define the basic tree structure
  • planner.h: define the planning action

src

  • rrt.cpp
  • planner.cpp: plan the motion. I use Euler distance to find the nearest node —— rrtPlanner
  • collision_detect.cpp: provide the service of collision detection —— collision_detection_srv
  • environment_publisher.cpp: subscribe the world information published by node rrtPlanner, and then send that to the server ellipsoid_point_gen_srv, publish the obtained 2D points to be plotted —— environment_pub
  • graph_publisher.cpp: subscribe the graph information published by node rrtPlanner, and then publish—— graph_pub
  • trajectory_publisher.cpp: subscribe the trajectory information published by node rrtPlanner, and then send that to the server ellipsoid_point_gen_srv, publish the obtained 2D points to be plotted —— trajectory_pub
  • ellipsoid_point_gen.cpp: a server whose input is ellipsoid msg and position msg and output is pointsArray msg describing the boundary of the ellipsoid —— ellipsoid_point_gen_srv

Run the Demo

RVIZ configuratoin

Global Optional
  • Fixed Frame = “/root”
Marker
  • arena
  • obstacle0
  • obstacle1
  • robot
  • trajectory
  • graph

Commands

after catkin_make && source devel/setup.bash

  • run the server
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2
rosrun rrt_implement ellipsoid_point_gen_srv
rosrun rrt_implement collision_detection_srv
  • run the rrt planner
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rosrun rrt_implement rrtPlanner
  • run the publisher
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rosrun rrt_implement environment_pub
rosrun rrt_implement trajectory_pub
  • run rviz
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rosrun rviz rviz

Running Result

Demo

Collision Detection

To achieve high speed, I did not call the collision detection libraries such as FCL. I just used a simple and rough method. Assume that $A$, $B$ is the center of two ellipsoids, respectively, and their distance is D. The “radius”s of the two ellipsoids in the direction of $\overrightarrow{AB}$ is $R$ and $r$, respectively. Thus, the requirement of the two ellipsoids is seperate is $D>R+r$; the requirement of the ellipsoid $B$ is in ellipsoid $A$ entirely is $D<R-r$.

As this is just the requirement, sometimes this method would fail.
An Example of Failure

Acknowledgement

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