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Jerry J. Hunter

dblp:230/7032 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1991
—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
Robot manipulation · 75% Motion planning and robot control · 25%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › contact-rich manipulation
contact formation
0.011991
A framework for planning dexterous manipulation · ICRA 1991
Robotics › Robot manipulation
contact modeling
0.011991
A framework for planning dexterous manipulation · ICRA 1991
Robotics › Robot manipulation
dexterous manipulation
0.011991
A framework for planning dexterous manipulation · ICRA 1991
Robotics › Motion planning and robot control › motion planning
manipulation planning
0.011991
A framework for planning dexterous manipulation · ICRA 1991

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

two-point boundary value problem · 0.0contact formation tree · 0.0
YearPublicationVenuePosition
1991 A framework for planning dexterous manipulation
abstract
The authors present a general methodology based on R.S. Desai's (1988) concept of contact formations and combine it with a model of contact mechanics to solve the dexterous manipulation planning problem. The model of contact mechanics supports the analysis of contact situations with multiple sliding contacts, allowing it to solve problems not solvable if only rolling contacts are allowed. Based on the proposed methodology, a planner would effectively solve two-point boundary value problems by using contact formation transitions to discretize the configuration space of, for example, a hand/object system. Within each discrete cell, or contact formation a model of contact mechanics is used to generate trajectories joining the cells and building a contact formation tree. If a solution exists, the tree grows until it contains a path from the initial grasp to the goal grasp. Then the individual input trajectories (assigned to the arcs of the tree) are combined to generate the complete manipulation trajectories.>
Jeffrey C. Trinkle, Jerry J. Hunter
ICRA2