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Degao Li

dblp:30/5744 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 1997
0000-0002-9235-8864ORCID · corroborated

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-authorApplied, 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
2 papers
Motion planning and robot control · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control
redundant manipulator control		 0.021997
A new method of peak torque reduction with redundant manipulators · IEEE Trans. Robotics Autom. 1997
Peak torque reduction with redundant manipulators · ICRA 1996
Robotics › Motion planning and robot control › robot control › optimization-based control
torque optimization		 0.021997
A new method of peak torque reduction with redundant manipulators · IEEE Trans. Robotics Autom. 1997
Peak torque reduction with redundant manipulators · ICRA 1996
Robotics › Motion planning and robot control
trajectory optimization		 0.011997
A new method of peak torque reduction with redundant manipulators · IEEE Trans. Robotics Autom. 1997

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

velocity field optimization · 0.0joint acceleration minimization · 0.0velocity and acceleration optimization · 0.0
YearPublicationVenuePosition
1997 A new method of peak torque reduction with redundant manipulators
abstract
A new method aiming at reducing peak torques is developed in this paper for kinematically redundant manipulators. The method considers the contributions of both velocity and acceleration to the joint torque. Instead of minimizing the joint torque or kinetic energy at the current station, the method always uses the current torque to approach an optimum velocity of the following station, which, along with joint acceleration, minimizes the torque of the following station, while at the same time keeps the current torque within the limits. Simulations are conducted for three cases and the results show the clear superiority of the proposed method over the conventional torque optimization and energy minimization methods.
Degao Li, Andrew A. Goldenberg, Jean W. Zu
 IEEE Trans. Robotics Autom.1
1996 Peak torque reduction with redundant manipulators
abstract
A new method aiming at reducing peak torques is developed in this paper for kinematically redundant manipulators. The method considers the contributions of both velocity and acceleration to the joint torque. Instead of minimizing the joint torque or kinetic energy at the current station, the method always uses the current torque to approach an optimum velocity of the following station, which, along with joint acceleration, minimizes the torque of the following station, while at the same time keeps the current torque within the limits. Simulations are conducted and the results show the clear superiority of the proposed method over the torque optimization method (Hollerbach & Suh 1987) and the energy minimization method (Khatib 1983).
Degao Li, Andrew A. Goldenberg, Jean W. Zu
 ICRA1