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Verifying Performance for Autonomous Robot Missions with Uncertainty
This work proposes an approach to verifying robot missions that shifts the focus from state-based analysis onto the solution of a set of flow equations (Lyons et al. 2012), and presents three validation results that show this approach has strong predictive power; that is, that the verifications it produces can be trusted.
Homing with stereovision
The algorithm, Homing with Stereovision (HSV), utilizes a stereo camera mounted on a pan-tilt unit to build composite wide-field stereo images and estimate distance and orientation from the robot to the goal location.
Performance Verification for Behavior-Based Robot Missions
- D. Lyons, R. Arkin, Shu Jiang, Tsung-Ming Liu, P. Nirmal
- Computer ScienceIEEE Trans. Robotics
- 20 May 2015
An approach based on behavior-based controllers in a process-algebra framework that avoids state-space combinatorics is presented here, and verification of the robot program in the uncertain environment is reduced to a filtering problem for a Bayesian network.
Navigation of uncertain terrain by fusion of information from real and synthetic imagery
This work extends ADAPT, a cognitive robotics architecture that incorporates 3D simulation and image fusion, to allow the robot to predict the behaviour of physical phenomena, such as falling masonry, and take actions consonant with long-term goals.
Visual homing with a pan-tilt based stereo camera
A visual homing method using scale change information (Homing in Scale Space, HiSS) from SIFT is developed that uses stereo data, resulting in better homing performance and is compared with HiSS in a set of indoor trials.