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Thomas H. Speeter

dblp:90/3446 · DBLP profile ↗
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3ranked-venue papers
2as 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 · 2 · 1 first-authorSystems, architecture and hardware · 2 · 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
3 papers
Robot manipulation · 54% Motion planning and robot control · 46%
Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
dexterous manipulation
0.021991
Primitive based control of the Utah/MIT dextrous hand · ICRA 1991
Modal state position controller for the Utah/MIT dextrous hand · IEEE Trans. Robotics Autom. 1990
Robotics › Motion planning and robot control › motion planning
motion primitives
0.011991
Primitive based control of the Utah/MIT dextrous hand · ICRA 1991
Robotics › Motion planning and robot control › robot control › compliant motion control
hybrid position/force control
0.011990
Modal state position controller for the Utah/MIT dextrous hand · IEEE Trans. Robotics Autom. 1990
Robotics › Robot manipulation › grasping › multifingered hand
multifingered hand control
0.011990
Modal state position controller for the Utah/MIT dextrous hand · IEEE Trans. Robotics Autom. 1990
Robotics › Motion planning and robot control
robot control
0.011989
Transformation of human hand positions for robotic hand control · ICRA 1989
Robotics › Robot manipulation › grasping
multifingered hand
0.011991
Primitive based control of the Utah/MIT dextrous hand · ICRA 1991
Human-robot interaction
teleoperation
0.011989
Transformation of human hand positions for robotic hand control · ICRA 1989

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

kinematic transformation · 0.0motion primitive abstraction · 0.0joint position control · 0.0modal state control · 0.0hybrid control · 0.0
YearPublicationVenuePosition
1991 Primitive based control of the Utah/MIT dextrous hand
abstract
An abstraction of dextrous manipulation and a control scheme for the Utah/MIT dextrous hand is described. The abstraction of robotic manipulation is based on motion primitives. Each primitive represents a small, coordinated set of joint motions that performs a distinct functional task. Primitives are defined as sequences of joint position changes that, when executed, cause functionally significant motion of the fingers. By defining the primitives as changes in position, rather than as absolute position trajectories, the ability to execute a primitive from any pose of the hand is gained. Hand programming language (HPL), a language and execution environment supporting the primitive abstraction, has been developed. Programming in HPL allows the user to describe dextrous manipulation tasks at a high level, insulated from the complex multiprocessing hierarchy controlling the hand.>
Thomas H. Speeter
ICRA1
1990 Modal state position controller for the Utah/MIT dextrous hand
abstract
Control of multifingered robotic hands is a natural example of hybrid control in which contact forces must be controlled without exceeding force thresholds while the fingers are moved to impart motion to an object. A modal state position control algorithm is described which is suited for hybrid manipulation tasks. Position tracking is robust, allowing force control to be executed in parallel according to task requirements. Hybrid control is achieved by the summed actions of the primary position controller and one or more secondary force controllers. The position control algorithm is outlined for both joint-space and Cartesian-space applications. Implementation and performance issues on the Utah/MIT dextrous hand are discussed.>
Thomas H. Speeter
IEEE Trans. Robotics Autom.1
1989 Transformation of human hand positions for robotic hand control
abstract
A method for using the human hand as a multidegree-of-freedom teaching device is described. The algorithm is based on a functional analysis of the human hand and results in an algebraic transformation of human hand positions to corresponding positions in a target domain. The target domain should be of lower dimensionality (fewer degrees of freedom) than the human hand but is not constrained in any other way. The target described here is a sixteen-degree-of-freedom robotic hand, with four fingers of four joints each. The target need not, however be a handlike device but, for each use, should have a kinematic structure with poses similar in functionality to natural poses of the human hand.>
Lucy Y. Pao, Thomas H. Speeter
ICRA2