1 April 1991 Computing motion parameters from sparse multisensor range data for telerobotics
Author Affiliations +
Proceedings Volume 1383, Sensor Fusion III: 3D Perception and Recognition; (1991) https://doi.org/10.1117/12.25248
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States
Abstract
Computing object motion from time-varying multi-sensor data and fusing this data into a coherent map of the object and/or its environment are important problems in robotics. In this paper, we present a new algorithm for motion estimation from sparse range data acquired from multiple sensors namely, a stereo camera system and an array of laser range finders. The motion estimates from this algorithm are input to a Kalman filter based state estimator for continuosly tracking a free-flying object in space under zero-gravity conditions.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Baba C. Vemuri, Baba C. Vemuri, G. Skofteland, G. Skofteland, "Computing motion parameters from sparse multisensor range data for telerobotics", Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); doi: 10.1117/12.25248; https://doi.org/10.1117/12.25248
PROCEEDINGS
12 PAGES


SHARE
RELATED CONTENT

Kalman filter vs. IMM estimator when do we need...
Proceedings of SPIE (July 12 2000)
Method for registration of 3-D shapes
Proceedings of SPIE (April 29 1992)
Fusion of inertial and vision data for accurate tracking
Proceedings of SPIE (January 13 2012)
Post-update compensation (PUC) with maneuver indicator
Proceedings of SPIE (May 11 2009)

Back to Top