| Date post: | 20-Dec-2015 |
| Category: |
Documents |
| View: | 219 times |
| Download: | 0 times |
Laboratory for Perceptual Robotics – Department of Computer Science
Whole-Body Collision-Free Motion Planning
Brendan BurnsLaboratory for Perceptual Robotics
University of Massachusetts Amherst
2Laboratory for Perceptual Robotics – Department of Computer Science
Why motion planning?
The real world is complicated
Collisions are hazardous
Mobility
3Laboratory for Perceptual Robotics – Department of Computer Science
How to motion plan?
Configuration space is big! (exponential) Exact methods are intractable Sampling-Based Planning (PRM)
4Laboratory for Perceptual Robotics – Department of Computer Science
Probabilistic Roadmap PlanningKavraki & Overmars 1996
?
5Laboratory for Perceptual Robotics – Department of Computer Science
12
3
6
7
8
9
5 4
10
6
3 8
942
[1..5] [7..10]
[1..2][4..5] [9..10]
6Laboratory for Perceptual Robotics – Department of Computer Science
Structure & Exploration
Identify the structure to expect
Acquire knowledge about structure
Exploit understanding as a guide
7Laboratory for Perceptual Robotics – Department of Computer Science
Models
8Laboratory for Perceptual Robotics – Department of Computer Science
Predictive Models
9Laboratory for Perceptual Robotics – Department of Computer Science
Active Sampling
10Laboratory for Perceptual Robotics – Department of Computer Science
Predictive Edge Checking
Edge checking is expensive
Our predictive model already exists
Construct a predictive roadmap
11Laboratory for Perceptual Robotics – Department of Computer Science
Predictive Roadmaps
12Laboratory for Perceptual Robotics – Department of Computer Science
Path Extraction
13Laboratory for Perceptual Robotics – Department of Computer Science
Path Extraction
14Laboratory for Perceptual Robotics – Department of Computer Science
Path Extraction
15Laboratory for Perceptual Robotics – Department of Computer Science
Path Extraction
16Laboratory for Perceptual Robotics – Department of Computer Science
Path Extraction
17Laboratory for Perceptual Robotics – Department of Computer Science
Experiments
18Laboratory for Perceptual Robotics – Department of Computer Science
0
20
40
60
80
100
120
Uniform Bridge Active Predictive
Guided Sampling Path ExtractionEdge Validation Collision CheckRoadmap Building
9-DOF
19Laboratory for Perceptual Robotics – Department of Computer Science
0
20
40
60
80
100
120
140
Uniform Bridge Active Predictive
Guided Sampling Path ExtractionEdge Validation Collision CheckRoadmap Building
12-DOF
20Laboratory for Perceptual Robotics – Department of Computer Science
Coming Soon…
21Laboratory for Perceptual Robotics – Department of Computer Science
Stop
22Laboratory for Perceptual Robotics – Department of Computer Science
Models
23Laboratory for Perceptual Robotics – Department of Computer Science
Optimal Sampling
24Laboratory for Perceptual Robotics – Department of Computer Science
Optimal Sampling
?
25Laboratory for Perceptual Robotics – Department of Computer Science
Active Sampling
26Laboratory for Perceptual Robotics – Department of Computer Science
Models
An approximate model of our current understanding
Predicts the state of unobserved configuration-space
Locally Weighted Regression (Atkeson et al.) Others are possible
27Laboratory for Perceptual Robotics – Department of Computer Science
Active Sampling
Our current understanding suggests areas of improvement
Sample to reduce maximize the expected reduction in model variance (Cohn et al.)
Direct sampling in proportion to complexity
