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Wade W. Wilson

dblp:126/4784 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1996
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

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 · 75% Robot manipulation · 25%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › compliant motion control
hybrid position/force control
0.011996
Synergy-based learning of hybrid position/force control for redundant manipulators · ICRA 1996
Robotics › Robot manipulation
redundant manipulator
0.011996
Synergy-based learning of hybrid position/force control for redundant manipulators · ICRA 1996
Robotics › Motion planning and robot control
robot control
0.011996
Synergy-based learning of hybrid position/force control for redundant manipulators · ICRA 1996
Robotics › Motion planning and robot control › whole-body control
synergy-based control
0.011996
Synergy-based learning of hybrid position/force control for redundant manipulators · ICRA 1996

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

reinforcement learning · 0.0motor synergies · 0.0
YearPublicationVenuePosition
1996 Synergy-based learning of hybrid position/force control for redundant manipulators
abstract
Describes an intelligent control architecture designed to endow human-like capabilities to robots and report experimental results that demonstrate the utility of this architecture in controlling a redundant dynamic manipulator in a hybrid position/force control task. Motor synergies that arise when control of a subset of the available degrees of freedom is coupled and coordinated to accomplish specific task sub-goals are used to simplify the problem, of controlling redundant systems by reducing the dimensionality of the control space. Using synergies as a basis control set gives the controller the general ability to execute novel tasks in unstructured environments. In addition, the rapid learning capabilities of the controller permit refinement of control through the acquisition of skilled control with practice.
Vijaykumar Gullapalli, Jack Gelfand, Stephen H. Lane, Wade W. Wilson
ICRA4