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Ruibo He

dblp:83/8504 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Motion planning and robot control · 100%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot calibration
kinematic parameter identification
0.112010
Kinematic-Parameter Identification for Serial-Robot Calibration Based on POE Formula · IEEE Trans. Robotics 2010
Robotics › Motion planning and robot control
robot calibration
0.112010
Kinematic-Parameter Identification for Serial-Robot Calibration Based on POE Formula · IEEE Trans. Robotics 2010
Robotics › Motion planning and robot control
robot control
0.112010
Kinematic-Parameter Identification for Serial-Robot Calibration Based on POE Formula · IEEE Trans. Robotics 2010
Robotics › Motion planning and robot control › robot calibration
serial robot calibration
0.112010
Kinematic-Parameter Identification for Serial-Robot Calibration Based on POE Formula · IEEE Trans. Robotics 2010

Methods — techniques the papers use, named apart from their topics

error modeling · 0.2product-of-exponentials formula · 0.1product of exponentials formula · 0.1
YearPublicationVenuePosition
2010 Kinematic-Parameter Identification for Serial-Robot Calibration Based on POE Formula
abstract
This paper presents a generic error model, which is based on the product of exponentials (POEs) formula, for serial-robot calibration. The identifiability of parameters in this error model was analyzed. The analysis shows the following: 1) Errors in all joint twists are identifiable. 2) The joint zero-position errors and the initial transformation errors cannot be identified when they are involved in the same error model. With either or neither of them, three practicable error models were obtained. The joint zero-position errors are identifiable when the following condition is satisfied: Coordinates of joint twists are linearly independent. 3) The maximum number of identifiable parameters is 6n+ 6 for ann-degree-of-freedom (DOF) generic serial robot. Simulation results show the following: 1) The maximum number of identifiable parameters is 6r+ 3t+ 6, whereris the number of revolute joints, andtis the number of prismatic joints. 2) All the kinematic parameters of the selective compliant assembly robot arm (SCARA) robot and programmable universal machine for assembly (PUMA) 560 robots were identified by using the three error models, respectively. The error model based on the POE formula can be a complete, minimal, and continuous kinematic model for serial-robot calibration.
Ruibo He, Yingjun Zhao, Shunian Yang, Shuzi Yang
IEEE Trans. Robotics1