Demo Data from EDBT 2026 / reviewers in the wild / expert
Wade W. Wilson
dblp:126/4784
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control › compliant motion control
hybrid position/force control |
0.0 | 1 | 1996 | Synergy-based learning of hybrid position/force control for redundant manipulators · ICRA 1996 |
Robotics › Robot manipulation
redundant manipulator |
0.0 | 1 | 1996 | Synergy-based learning of hybrid position/force control for redundant manipulators · ICRA 1996 |
Robotics › Motion planning and robot control
robot control |
0.0 | 1 | 1996 | 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 |
0.0 | 1 | 1996 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | Synergy-based learning of hybrid position/force control for redundant manipulatorsabstractDescribes 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 |
ICRA | 4 |