using a prm planner to compare centralized and decoupled planning for multi-robot systems
DESCRIPTION
Using a PRM Planner to Compare Centralized and Decoupled Planning for Multi-Robot Systems. By Gildardo Sánchez and Jean-Claude Latombe In Proc. IEEE Int. Conf. on Robotics and Automation 2002 Presented by Melvin Zhang. Overview. Motivation Coordinating multiple robots Centralized planning - PowerPoint PPT PresentationTRANSCRIPT
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NUS CS5247
Using a PRM Planner to Using a PRM Planner to Compare Centralized Compare Centralized
and Decoupled and Decoupled Planning for Multi-Planning for Multi-
Robot SystemsRobot Systems
By Gildardo Sánchez and Jean-Claude By Gildardo Sánchez and Jean-Claude LatombeLatombe
In Proc. IEEE Int. Conf. on In Proc. IEEE Int. Conf. on Robotics and Automation 2002 Robotics and Automation 2002
Presented by Melvin ZhangPresented by Melvin Zhang
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Overview Motivation Coordinating multiple robots Centralized planning Decoupled planning SBL planner Experiment setup Results Summary Comments
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Motivation Some industrial settings (spot welding) requires
4-10 robots with 20-60 dof each Manual programming
time consuming and error prone Multi robot planning can be classified as
centralized decoupled
Decoupled approach is prevalent, as lost of completeness is assumed to be small
How valid is this statement?
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Coordinating multiple robots (Demo)
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Coordinating multiple robots Assuming p robots with n dof each Centralized planning
Treat multiple robots as a single robot Plan in the composite C-space Complexity ~ enp
Decoupled planning Plan for each robot independently Coordinate them later Complexity ~ pen
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Centralized planning Reduce problem to planning for single robot Collisions between robots are self-collisions of
the single composite robot Advantages
Complete, if the underlying planner is complete
Drawbacks Computationally expensive, Not applicable when global state of all robots is
unknown
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Decoupled planning Plans path of each robot independently Coordinate them later Several schemes
Velocity turning Robot prioritization
Advantages Faster as C-space has fewer dimensions
Drawbacks Incomplete No coordinated trajectory of paths found in first phase
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Decoupled planning – Two schemes Velocity tuning
Separately plan a path of each robot to avoid collision with obstacles
Compute the trajectory of the robots to avoid inter-robot collision
Global coordination – plan in [0,1]p
Pairwise coordination – plan in [0,1]2
After path is fixed, dof of each robot is 1
Pairwise coordination plan s1 and s2
plan s1,2 with s3, ... plan s1,...,n-1 with sn
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Decoupled planning – Two schemes Robot prioritization
Plan path of the first robot in its C-space Plan trajectory of ith robot assuming that robots
1,…,i-1 are moving obstacles
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Decoupled planning - Incompleteness Initial configuration Goal configuration
Paths generated in first phase No coordinated solution found in second phase
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SBL planner Single-query
Roadmap is used to answer a single planning query
Bi-directional Grow a tree of milestones from both start and end
configuration
Lazy in checking collision Avoid unnecessary collision checking on edges 4-40 times faster than classical single-query
bidirectional PRM planner
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Characteristics of SBL planner
Plot of number of failure vs max milestones allowed (S) Two thresholds Smin and Smax for a problem instance
If (S < Smin) planner fails consistently
If (S > Smax) planner succeeds consistently
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Experiment setup Planners
Centralized planning (C-SBL) Decoupled planning, global coordination (DG-SBL) Decoupled planning, pairwise coordination (DP-SBL)
Three problem instances, {PI, PII, PIII} Number of robots involved, {2, 4, 6} Number of runs
100 for C-SBL 20 for DG-SBL and DP-SBL
For each call to the SBL planner, at most 50,000 milestones are allowed
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Problem I
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Problem II
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Problem III
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Results – C-SBL Result for C-SBL
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Results – Failure rate
Rate of failure increases sharply for 4 and 6 robots Failure occurs during coordination Successful run of decoupled planner, no of milestones smaller than
50,000 -> failure due to incompleteness of decoupled approach
Comparison of failure rate
0
10
20
30
40
50
60
70
80
90
PI-2 PI-4 PI-6 PII-2 PII-4 PII-6 PIII-2 PIII-4 PIII-6
Problem instance
Per
cen
tag
e o
f fa
ilu
res
DG-SBL
DP-SBL
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Results – Running time
Running time for all 3 planners are comparable Centralize planning is feasible using SBL planner
Comparison of running time
0
50
100
150
200
250
300
350
400
450
500
PI-2 PI-4 PI-6 PII-2 PII-4 PII-6 PIII-2 PIII-4 PIII-6
Problem instance
Ru
nn
ing
tim
e
C-SBL
DG-SBL
DP-SBL
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Summary Decoupled planning may not find a solution
when tight coordination is required Loss of completeness is significant in practice
Using SBL, planning time for decoupled and centralized planning is comparable Centralized planning is technically feasible
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Comments Tight coordination is specified using specific
problem instances Similar to the concept of expansiveness, is it possible
to develop some characterization of “tight coordination”?
Centralized and decoupled can be viewed as two extremes of coordination Can we find a continuum of planners in which the
level of coordination can be parameterized? One idea is to use a hierarchy of robots
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Thank you for listening Questions ?
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