Motion estimation with cooperatively working multiple robots

We have investigated the performance of simultaneously estimating the 3D motion and structure for navigation when the scale information is obtained by utilizing the cooperative efforts of multiple robots. The method determines the relative positions of robots by tracking a specific geometric feature that is part of their structure, and then uses the extended Kalman filter to estimate the motion and structure. For implementation we used two CRAWLER Scouts, and performed several experiments to explore the effects of cooperative running of robots on the motion estimation.

Authors

• Güleser Kalayci Demir
• Richard M. Voyles
• Amy C. Larson

Keywords

• Motion estimation
• Robot kinematics
• Cameras
• Robot vision systems
• Tracking
• Robot sensing systems
• Computer science
• Crawlers
• Layout
• Orbital robotics
• Multiple Robots
• Specific Characteristics
• 3D Structure
• Kalman Filter
• Geometric Features
• Extended Kalman Filter
• 3D Motion
• Covariance Matrix
• Image Features
• Scaling Factor
• Image Plane
• Angular Velocity
• Local Point
• Focal Length
• Feature Points
• Translational Motion
• Edge Detection
• Coordinate Transformation
• 3D Position
• Feature Tracking
• Successive Frames
• Camera Motion
• Coordination Features
• Robot Motion
• Planetary Exploration
• Error Covariance Matrix
• Robot Model
• Position Information