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Niels Smaby

dblp:13/4564 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none

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

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2

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 · 61% Robot manipulation · 39%
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
0.012000
An Overview of Dexterous Manipulation · ICRA 2000
Robotics › Motion planning and robot control › robot control
operational space control
0.011999
ProVAR Assistive Robot System Architecture · ICRA 1999
Robotics › Motion planning and robot control
robot control
0.011999
ProVAR Assistive Robot System Architecture · ICRA 1999
Human-robot interaction
assistive robotics
0.011999
ProVAR Assistive Robot System Architecture · ICRA 1999
Robotics › Robot manipulation › grasping
grasp planning
0.012000
An Overview of Dexterous Manipulation · ICRA 2000
Robotics › Motion planning and robot control
motion planning
0.012000
An Overview of Dexterous Manipulation · ICRA 2000
Human-robot interaction › assistive robotics
assistive manipulation
0.011999
ProVAR Assistive Robot System Architecture · ICRA 1999

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

operational space formulation · 0.0direct-manipulation simulation · 0.0kinematic modeling · 0.0contact force analysis · 0.0
YearPublicationVenuePosition
2000 An Overview of Dexterous Manipulation
abstract
Presents an overview of research in dexterous manipulation. We first define robotic dexterous manipulation in comparison to traditional robotics and human manipulation. Next, kinematics, contact types and forces are used to formulate the dexterous manipulation problem. Dexterous motion planning is described, which includes grasp planning and quality measures. We look at mid- and low-level control frameworks, and then compare manipulation versus exploration. Finally, we list accomplishments in the different areas of dexterous manipulation research, and highlight important areas for future work.
Allison M. Okamura, Niels Smaby, Mark R. Cutkosky
ICRA2
1999 ProVAR Assistive Robot System Architecture
abstract
This paper describes the implementation of a robot control architecture designed to combine a manipulation task design environment with a motion controller that uses the operational space formulation to define and implement arm trajectories and object manipulation. The ProVAR desktop manipulation system is an assistive robot for individuals with a severe physical disability, such as quadriplegia as a result of a high-level spinal cord injury. ProVAR allows non-technical operators access to the robot's capabilities through a direct-manipulation simulation/preview user interface. The novel interface concept is based on two built-in characters to play the roles of helpful consultant and down-to-earth robot arm. This team-based interface concept was chosen to maximize user performance and comfort in controlling the inherently complex mechatronic technology. This paper describes our design decisions and rationale.
H. F. Machiel Van der Loos, J. Joseph Wagner, Niels Smaby, Kyong-Sok Chang, O. Madrigal, Larry J. Leifer, Oussama Khatib
ICRA3