my summer at willow garage - ros.org · my summer goals sbpl arm planner continue development of...
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My Summer at Willow Garage
Benjamin CohenUniversity of Pennsylvania
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The Bosses
Dr. Sachin Chittamy mentorProfessor Maxim Likhachevmy advisor
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My Summer Goals
SBPL Arm Plannercontinue development of new algorithmintegrate into move_armperform tabletop manipulationpublish SBPL Door Planner(Sachin did all of the integration. I'm working on the algorithm and debugging it with him)
continue development of algorithmmake a sweet videopublish
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SBPL Arm Planner
Goal:Develop a motion planner for robotic manipulation that can robustly plan paths in cluttered environments.
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Why not run IK and plan to a known valid joint configuration?
IK is very fast but may not find the 'best' solutionmay find a visually awkward solutionmay orient the arm very close to obstaclesmay choose a solution very close to joint limits
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Why not run IK and plan to a known valid joint configuration? (cont'd)
Let the planner optimize the goal joint configuration according to the desired cost function:length of pathsmoothnessdistance from obstacleskeep away from joint limits
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Graph Construction
similar to lattice based planners in planning dynamically feasible trajectories
a discretization of the configuration space into a set of states, the edges that connect the starts are dynamically feasible
edges are pre-defined motion primitives
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Motion Primitives
7 basic primitives:
m1: shoulder pan m2: shoulder pitch m3: upper arm roll
m4: elbow pitch m5: forearm roll m6: wrist pitch
m7: wrist roll
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Costs
Smoothing Costminimize change in velocities between stateskeep the same joint(s) moving if possible
Action Costminimize the number of actions to the goal
Distance Costapply a cost for planning close to obstacles
c s , s ' =ccells ' waction∗cactions , s ' w smooth∗csmooth s , s '
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Heuristic
3D Dijkstra searchrobust to obstacles
pre-computeddirects the end effector to the goal pose
difference in orientation of the end effector
Goal
Dijkstra Shortest Path
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ARA : Anytime Random A*
is consistentguarantees completeness'anytime results' – can trade-off path cost vs. computation time
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ARA : Anytime Random A*
ARA* finds a feasible solution quickly and then continually works on improving it until the allocated time runs out.ARA* uses an admissible heuristic (a bound on the plan-execution cost) to focus its searchEach solution comes with a bound, ε, on its sub-optimality: cost(solution) ≤ ε·cost(optimal solution)
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Features
given multiple goals, find the path to goal pose with lowest costplan to 'goal region'plan with path constraints, such as:keep a cup uprightdon't obstruct field of view of forearm cameras (future work)
plan to a goal pose in collision, capable of manipulation (future work)
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Drawbacks
high dependency on the heuristic functionlocal minimadoesn't describe kinematics of the arm
high dimensionality slows down the searchdiscretized paths
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Future Work
learn a set of motion primitives with good coverage of the workspace and natural looking movementadd randomization to escape local minimaR* is an A* type search with randomization
research smoothing methods
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SBPL Door Planner
Goal:open doorsinward and outward opening doorsright handed and left handed doorswith collision avoidanceguaranteed feasibility
Method:ARA* in a 4-Dimensional state space{x,y,theta,door interval}door interval: {0,1} (open or closed)
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Other Packages
Robot Voxelizer (sandbox/robot_voxelizer)
wrapper around Ioan's planning modelsvoxelize robot bodies, meshes, shapes
PM Wrapper (planning_research/pm_wrapper)
wrapper around Ioan's planning_monitor classeasy collision checking, collision map manipulation
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Other Packages (cont'd)
Arm Command Tool (sandbox/move_arm_tools)
'safe' movement with move_arm'unsafe' movement for tabletop manipulation
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Thank You!
Scott & SteveSachinMaxIoan and MrinalEveryone else!
thanks!