Demo Data from VLDB 2026 / reviewers in the wild / expert
Erez Krimsky
dblp:274/9681
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control
actuator control |
0.4 | 1 | 2020 | Optimal Control of an Energy-Recycling Actuator for Mobile Robotics Applications · ICRA 2020 |
Robotics › Motion planning and robot control › robot control
optimal control |
0.4 | 1 | 2020 | Optimal Control of an Energy-Recycling Actuator for Mobile Robotics Applications · ICRA 2020 |
Robotics › Motion planning and robot control
robot control |
0.4 | 1 | 2020 | Optimal Control of an Energy-Recycling Actuator for Mobile Robotics Applications · ICRA 2020 |
Robotics › Motion planning and robot control
trajectory optimization |
0.4 | 1 | 2020 | Optimal Control of an Energy-Recycling Actuator for Mobile Robotics Applications · ICRA 2020 |
Energy-efficient computing
power management |
0.1 | 1 | 2020 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Optimal Control of an Energy-Recycling Actuator for Mobile Robotics ApplicationsabstractActuator 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 |
ICRA | 1 |