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System Integration and System Integration and Experimental ResultsExperimental Results
Intelligent Robotics Research Centre (IRRC)
Department of Electrical and Computer Systems Engineering
Monash University, Australia
Visual Perception and Robotic Manipulation
Springer Tracts in Advanced Robotics
Chapter 7Chapter 7
Geoffrey Taylor
Lindsay Kleeman
2Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
OverviewOverview
• Stereoscopic light stripe scanning
• Object Modelling and Classification
• Multicue tracking (edges, texture, colour)
• Visual servoing
• Real-world experimental manipulation tasks with an upper-torso humanoid robot
3Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
MotivationMotivation
• To enable a humanoid robot to perform manipulation tasks in a domestic environment:– A domestic helper for the elderly and disabled
• Key challenges:– Ad hoc tasks with unknown objects
– Robustness to measurement noise/interference
– Robustness to calibration errors
– Interaction to resolve ambiguities
– Real-time operation
4Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
ArchitectureArchitecture
5Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Light Stripe ScanningLight Stripe Scanning
• Triangulation-based depth measurement.
Stripe generatorCamera
Scannedobject
B
D
6Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Stereo Stripe ScannerStereo Stripe Scanner
• Three independent measurements provide redundancy for validation.
Leftcamera
L
Scannedobject
2b
RightcameraR
Laserdiode
X
xL xR
Left imageplane
Right imageplane
θ
7Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Reflections/Cross TalkReflections/Cross Talk
8Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Single Camera ResultSingle Camera Result
Single camera scanner Robust stereoscopic scanner
9Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
3D Object Modelling3D Object Modelling
• Want to find objects with minimal prior knowledge.– Use geometric primitives to represent objects
• Segment 3D scan based on local surface shape.
Surface type classification
10Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
SegmentationSegmentation
• Fit plane, sphere, cylinder and cone to segments.
• Merge segments to improve fit of primitives.
Raw scan Finalsegmentation
Surface typeclassification
Geometricmodels
11Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Object ClassificationObject Classification
• Scene described by adjacency graph of primitives.
• Objects described by known sub-graphs.
12Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Modeling ResultsModeling Results
• Box, ball and cup:
Raw colour/range scan Textured polygonal models
13Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Multi-Cue TrackingMulti-Cue Tracking
• Individual cues are only robust under limited conditions:– Edges fail in low contrast,
distracted by texture
– Textures not always available, distracted by reflections
– Colour gives only partial pose
• Fusion of multiple cues provides robust tracking in unpredictable conditions.
14Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Tracking FrameworkTracking Framework
• 3D Model-based tracking: models modelled from light stripe range data.
• Colour (selector), edges and texture (trackers) are measured simultaneously in every frame.
• Measurements fused in Extended Kalman filter:– Cues interact with state through measurement models
– Individual cues need not recover the complete pose
– Extensible to any cues/cameras for which a measurement model exists.
15Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Colour CuesColour Cues
• Filter created from colour histogram in ROI:– Foreground colours promoted in histogram
– Background colours supressed in histogram
Captured image used to generate filter
Output of resulting filter
16Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Edge CuesEdge Cues
Combine with colour to get silhouette edges
Sobel mask directional
edges
Fitted edges
Predicted projected edges
17Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Texture CuesTexture Cues
Rendered prediction Feature detector Matched templates
Outlier rejection Final matched features
18Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Tracking ResultTracking Result
19Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Visual ServoingVisual Servoing
• Position-based 3D visual servoing (IROS 2004).
• Fusion of visual and kinematic measurements.
20Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Visual ServoingVisual Servoing
• 6D pose of hand estimated using extended Kalman filter with visual and kinematic measurements.
• State vector also includes hand-eye transformation and camera model parameters for calibration.
21Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Grasping TaskGrasping Task
• Grasp a yellow box without prior knowledge of objects in the scene.
22Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Grasping TaskGrasping Task
23Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Pouring TaskPouring Task
• Pour the contents of a cup into a bowl.
24Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Pouring TaskPouring Task
25Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
Smell ExperimentSmell Experiment
• Fusion of vision, smell and airflow sensing to locate and grasp a cup containing ethanol.
26Taylor and Kleeman, Visual Perception and Robotic Manipulation, Springer Tracts in Advanced Robotics
SummarySummary
• Integration of stereoscopic light stripe sensing, geometric object modelling, multi-cue tracking and visual servoing allows robot to perform ad hoc tasks with unknown objects.
• Suggested directions for future research:– Integrate tactile and force sensing
– Cooperative visual servoing of both arms
– Interact with objects to learn and refine models
– Verbal and gestural human-machine interaction