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Barry L. Burks

dblp:53/3567 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1995
—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 · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control
flexible manipulator control
0.021995
Tracking Control of the hydraulically Actuated Flexible Manipulator · ICRA 1995
Input Shaping Filter Methods for the Control of Structurally Flexible, Long-Reach Manipulators · ICRA 1994
Robotics › Motion planning and robot control
robot control
0.021995
Tracking Control of the hydraulically Actuated Flexible Manipulator · ICRA 1995
Input Shaping Filter Methods for the Control of Structurally Flexible, Long-Reach Manipulators · ICRA 1994
Robotics › Motion planning and robot control › robot control › actuator control
hydraulic actuator control
0.011995
Tracking Control of the hydraulically Actuated Flexible Manipulator · ICRA 1995
Robotics › Motion planning and robot control › robot control › vibration suppression
input shaping
0.011994
Input Shaping Filter Methods for the Control of Structurally Flexible, Long-Reach Manipulators · ICRA 1994
Robotics › Motion planning and robot control › robot control
vibration suppression
0.011994
Input Shaping Filter Methods for the Control of Structurally Flexible, Long-Reach Manipulators · ICRA 1994

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

shaping filter · 0.0pressure feedback · 0.0feedforward simulation filter · 0.0notch filtering · 0.0impulse shaping · 0.0fuzzy logic · 0.0feedforward simulation · 0.0
YearPublicationVenuePosition
1995 Tracking Control of the hydraulically Actuated Flexible Manipulator
abstract
The remediation of single-shell radioactive waste storage tanks is one of the urgent tasks of the Department of Energy that challenge state-of-the-art equipment and methods. The use of long-reach manipulators is being seriously considered for this remediation task. Because of high payload capacity and high length-to-cross-section ratio requirements, these long-reach manipulator systems are expected to use hydraulic actuators and to exhibit significant structural flexibility. The controller has been designed to compensate for the hydraulic actuator dynamics by using a load-compensated velocity feedforward loop and to increase the bandwidth by using a pressure feedback loop. Shaping filter techniques have been applied as a feedforward controller to avoid structural vibrations during operation. Among various types of shaping filter methods investigated an approach, referred to as a "feedforward simulation filter" that uses embedded simulation, has been presented.
Dong-Soo Kwon, Scott M. Babcock, Barry L. Burks, Reid L. Kress
ICRA3
1994 Input Shaping Filter Methods for the Control of Structurally Flexible, Long-Reach Manipulators
abstract
Within the Environmental Restoration and Waste Management Program of the US Department of Energy, the remediation of single-shell radioactive waste storage tanks is one of the areas that challenges state-of-the-art equipment and methods. Concepts that utilize long-reach manipulators are being seriously considered for this task. Due to high payload capacity and high length-to-cross-section ratio requirements, these long-reach manipulator systems are expected to exhibit significant structural flexibility. To avoid structural vibrations during operation, various types of shaping filter methods have been investigated. A robust notch filtering method and an impulse shaping method were used as simulation benchmarks. In addition to that, two very different approaches have been developed and compared. One new approach, referred to as a "feedforward simulation filter", uses imbedded simulation with complete knowledge of the system dynamics. The other approach, "fuzzy shaping method", employs a fuzzy logic method to modify the joint trajectory from the desired end-position trajectory without precise knowledge of the system dynamics.>
Dong-Soo Kwon, Dong-Hwan Hwang, Scott M. Babcock, Barry L. Burks
ICRA4