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Motion Planning Benchmarks | Algorithms & Applications Group
Algorithms & Applications Group
Motion Planning Puzzles
(aka benchmarks)

The models contained on this page represent our attempt to try to start a collection of benchmark problems that can be used to compare various motion planning algorithms. As such, these models are available for public, non-commercial use provided that appropriate reference is made to the source/creator of the model. Also, if you have any models that you could contribute to this effort, please let us know and we will be happy to post them on this page.
 Alpha Puzzle Provided by Boris Yamrom, GE Corporate Research & Development Center The alpha puzzle benchmark is a motion planning problem containing a narrow passage. The puzzle consists of two tubes, each twisted into an alpha shape; one tube is the obstacle and the other the moving object (robot). The objective is to separate the intertwined tubes. In order for the problem to be solved a complex set of translation and orientation movements need to take place within the narrow passage. Computationally the narrow passage needs to be adequately mapped which is a difficult problem as this valid space is fairly difficult to generate samples in. Animations: original version (scale 1.0) - Solved by OBRRT original version (scale 1.0) - Provided by James Kuffner simplified version (scale 1.5) simplified version (scale 1.5) Flange Problem Provided by GE Corporate Research & Development Center The flange benchmark is a motion planning problem containing a narrow passage. It is representative of a type of problem that might occur in a maintainabilty study of a mechicanical CAD design. The environment consists of a fixed rectangular part with a circular opening (the obstacle) and an elbow shaped curved pipe (the robot) that must be inserted into the opening in the obstacle. This problem requires generating a sliding motion where the obstacle and robot are nearly touching with the robot twisted into or out of the obstacle. Finding valid motions in this constrained space is a difficult problem with many approaches developed to find these portions of the space. Animations: original version (scale 1.0) (avi) - Solved by OBRRT original version (scale 1.0) (mp4) - Solved by OBRRT simplified version (scale 0.85) - Solved with Single Shot Motion Planning simplified version (scale 0.85) - Solved with haptic interaction in motion planning Box Folding Problem Created by Guang Song, Parasol Lab, Texas A&M University The box folding problem is a motion planning problem containing a narrow passage. The objective is to fold the articulated model into its final box shape. There are no external obstacles in the enviroment, but self-collision among the links (connected by revolute joints) must be avoided. Animations: Box folding (avi) Periscope Folding Problem Created by Guang Song, Parasol Lab, Texas A&M University The periscope folding problem is a motion planning problem containing a narrow passage. The objective is to fold the articulated model into its final periscope shape. There are no external obstacles in the enviroment, but self-collision among the links (connected by revolute joints) must be avoided. Animations: Periscope folding (large avi) Periscope folding (small avi) Pentomino Puzzle Created by Ian Remmler, Parasol Lab, Texas A&M University The Pentomino Puzzle environment was created to test disassembly planning methods. The puzzle is "solved" in its initial (assembled) configuration, and the goal is to disassemble the puzzle by moving each piece an arbitrary distance away from all other pieces. Animations: Pentomino Disassembly (avi) Bug-Trap Created by Parasol Lab, Texas A&M University The objective is to take the bug robot outside of the trap obstacle throught the narrow passage. Hedgehog Created by Vojta Vonasek at the Intelligent and Mobile Robotics Group, Department of Cybernetics, Czech Technical University The Hedgehog environment contains a few very difficult narrow passages that the robot (spiked sphere) must pass through to escape the cage. Serial Walls Created by Parasol Lab, Texas A&M University The Serial Walls environment consists of a set of walls (with openings) that the stick (the robot) has to traverse. Animations: Walls with linked robot - solved by Feature Sensitive Motion Planning. Walls with rigid body robot and additional obstacles in each chamber - solved by Feature Sensitive Motion Planning. S Tunnel Created by Parasol Lab, Texas A&M University The S tunnel environment consists of two elongated cubes. The obstacle is an elongated cube with a long narrow tunnel incisioned in it. The robot is another small cube. Z Tunnel Created by Parasol Lab, Texas A&M University The Z tunnel environment contains an obstacle with a single narrow passage shaped like a Z. The robot is a small cube. L Tunnel Created by Parasol Lab, Texas A&M University The L tunnel environment contains two L-shaped passages the robot (also L-shaped) must traverse. Animations: L-tunnel - solved by MAPRM. Bright Building Created by Parasol Lab, Texas A&M University The Bright Building environment contains the first 4 floors of HRBB. The building consists of many rooms, corridors, and stiarwells. Agents navigating in this environment must be able to extract paths quickly through the environment in order to perform certain behaviors. Animations: Evacuations behavior - for more information and animations visit our evacuation and direction work
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