Bayesian Probabilistic Stopping Test and Asymptotic Shortest Time Trajectories for Object Reconstruction with a Mobile Manipulator Robot

This paper proposes a Bayesian probabilistic stopping test for 3D object reconstruction with a mobile manipulator robot. Additionally, this work also presents an objective function to be optimized, which requires to find the time-optimal trajectories in the presence of obstacles for a non-holonomic...

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Bibliographic Details
Published in:Journal of intelligent & robotic systems 2022-08, Vol.105 (4), Article 82
Main Authors: Yervilla-Herrera, Heikel, Becerra, Israel, Murrieta-Cid, Rafael, Sucar, Luis Enrique, Morales, Eduardo F.
Format: Article
Language:English
Subjects:
Analysis
Artificial Intelligence
Bayesian analysis
Control
Electrical Engineering
End effectors
Engineering
Experiments
Manipulators
Mechanical Engineering
Mechatronics
Planning
Reconstruction
Robot arms
Robotics
Robotics industry
Robots
Sensors
Short Paper
Trajectory optimization
Unmanned aerial vehicles
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Summary:This paper proposes a Bayesian probabilistic stopping test for 3D object reconstruction with a mobile manipulator robot. Additionally, this work also presents an objective function to be optimized, which requires to find the time-optimal trajectories in the presence of obstacles for a non-holonomic robotic base satisfying visibility constraints at the sensing locations. The termination test together with a whole method for object reconstruction, is validated through comparisons with other termination criteria. Experiments in both simulation and with a physical mobile manipulator robot equipped with a sensor mounted on the arm’s end effector, are presented. On the basis of an experimental evaluation, it was found that the proposed objective function reduces the total reconstruction time, and that the proposed termination test achieves a good balance between the total number of sensing operations and the reconstruction percentage.
ISSN:0921-0296
1573-0409
DOI:10.1007/s10846-022-01696-z