1. On Multi-Arm Manipulation Planning
2012/10/5
On Multi-Arm Manipulation Planning
Presented by
Zijun Wei

2. 2012/10/5
Brief Introduction
Automatic generation of manipulation paths for multiple manipulators Different from classical path planning. Advantages: Larger area Heavier load More efficient Additional difficulty: what time; which arm; how to coordinate; how to grasp and regrasp
Basically an extension of what we learned on Wednesday
Actually there are more things to consider more things. For example, we may need to consider how to avoid collision; how to make all the manipulator work parallel and efficient

3. Problem Statement Definitions of terms(C-space formalization):
2012/10/5
Problem Statement
Definitions of terms(C-space formalization):
Similar to what we learned on Wednesday
Except:
1. 𝐶 𝑓𝑟𝑒𝑒 is actually 𝐶 𝑎𝑑𝑚𝑖𝑠𝑠𝑖𝑏𝑙𝑒
2. 𝐶 𝑔𝑟𝑎𝑠𝑝 𝑖𝑠 𝑖𝑛𝑐𝑙𝑢𝑑𝑒𝑑 𝑖𝑛 𝐶 𝑠𝑡𝑎𝑏𝑙𝑒
Goal: Compute a manipulation path between two input system configurations.
My understanding is that it’s incomplete because it could just represent the static part of the grasp
It’s for only one object

4. Assumptions & Simplifications
2012/10/5
Assumptions & Simplifications
Pick grasps from a finite predefined set of grasps.
Idealized the grasps that require 2 or more arms.
Based on an assumption that transit path is always available.
Only one object involved.
Each manipulator has a relatively non-obstructive configuration
畅想： give different weight to the different tasks: transfer/transit
Prior to a path generation, all arms that will not be used will be placed into this place. Also the algorithm will double check

5. 2012/10/5
Planning Approach
1. Focus solely on identifying a sequence of transfer subtasks that are guaranteed to be completed into transfer paths(modified RPP).
2. Define the transit paths based on transfer paths(Assumption, if not, return failure).
Note that identifying a series of subtasks first may lead to incompletion.
If we identify a series of subtasks first, we have no idea in advance whether all of the tasks can be performed or represented by a transit path or transfer path

6. Generating transfer tasks
2012/10/5
Generating transfer tasks
Algorithm: modified Randomized Path Planner
Based on GraspAssignments (grasp, robot, posture)
(Similar to Depth-First Traversal) modified RPP in order to check if there exists a grasp from the grasp set.

7. 2012/10/5
Note: The number regrasps along the generated path is minimal, but not shortest.

8. 2012/10/5
Detail and Comments
1. Get different postures for one grasp, thus acquiring different grasp assignments.
2. Set time limit for RPP.
3. Manipulators that are not used are posed at non-obstructive place
4. One arm can help Object maintain static
The change between two grids may not be smooth

9. Generating Transit Paths
Existence of transit paths corresponding transit tasks
More complex situations with intermediate grasps:
Breaking transit tasks into smaller subtasks
Allowing using arms not used in consecutive tasks

11. Limitations 1. Computational complexity increases rapidly
2. Modified RPP is only probabilistically compete.
3. Assumptions on availability of transit paths leads to failure.
4. Many assumptions that prevent the generalization and efficiency.
5. The path is not smooth.
6. Set of threshold on grid size

12. Future Work Verify in real world
2012/10/5
Future Work
Verify in real world
Regrasp by placing objects against obstacles.
Execute two consecutive transfer and transit paths if no collision
Incorporate torque constraints and dynamics issues in the planning process.
Personal Ideas:
Automatic generation of grasps by searching databases
More than one moveable object coordination
Involve obstacles to help deal with regrasps.
Several extensions:
Involve obstacles to help dealing with regrasps: when a regrasp required, we first pose the object on the nearest obstacle, then switch the graspers, then grasp it.
2. Combining the grasp assignment set to some online database in order to get more manipulation grasp