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Erez Krimsky

dblp:274/9681 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · unresolved

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

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 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
1 paper
Motion planning and robot control · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Energy-efficient computing · 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
actuator control
0.412020
Optimal Control of an Energy-Recycling Actuator for Mobile Robotics Applications · ICRA 2020
Robotics › Motion planning and robot control › robot control
optimal control
0.412020
Optimal Control of an Energy-Recycling Actuator for Mobile Robotics Applications · ICRA 2020
Robotics › Motion planning and robot control
robot control
0.412020
Optimal Control of an Energy-Recycling Actuator for Mobile Robotics Applications · ICRA 2020
Robotics › Motion planning and robot control
trajectory optimization
0.412020
Optimal Control of an Energy-Recycling Actuator for Mobile Robotics Applications · ICRA 2020
Energy-efficient computing
power management
0.112020
Optimal Control of an Energy-Recycling Actuator for Mobile Robotics Applications · ICRA 2020

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

optimal control · 0.9mixed-integer quadratic programming · 0.9
YearPublicationVenuePosition
2020 Optimal Control of an Energy-Recycling Actuator for Mobile Robotics Applications
abstract
Actuator power consumption is a limiting factor in mobile robot design. In this paper we introduce the concept of an energy-recycling actuator, which uses an array of springs and clutches to capture and return elastic energy in parallel with an electric motor. Engaging and disengaging clutches appropriately could reduce electrical energy consumption without sacrificing controllability, but presents a challenging control problem. We formulated the optimal control objective of minimizing actuator power consumption as a mixed-integer quadratic program (MIQP) and solved for the global minimum. For a given actuator design and a wide range of simulated torque and rotation patterns, all corresponding to zero net work over one cycle, we compared optimized actuator energy consumption to that of an optimized gear motor with simple parallel elasticity. The simulated energy-recycling actuator consumed less electrical energy: 57% less on average and 80% less in the best case. These results demonstrate an effective approach to optimal control of this type of system, and suggest that energy-recycling actuators could substantially reduce power consumption in some robotics applications.
Erez Krimsky, Steven H. Collins
ICRA1