Demo Data from EDBT 2026 / reviewers in the wild / expert
Yahya S. Khaligh
dblp:83/8366
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · none
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% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control
adaptive control |
0.1 | 1 | 2010 | Adaptive control of robot manipulators including actuator dynamics and without joint torque measurement · ICRA 2010 |
Robotics › Motion planning and robot control › robot control › trajectory tracking
motion tracking control |
0.1 | 1 | 2010 | Adaptive control of robot manipulators including actuator dynamics and without joint torque measurement · ICRA 2010 |
Robotics › Motion planning and robot control
robot control |
0.1 | 1 | 2010 | Adaptive control of robot manipulators including actuator dynamics and without joint torque measurement · ICRA 2010 |
Methods — techniques the papers use, named apart from their topics
backstepping · 0.1adaptive observer · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Adaptive control of robot manipulators including actuator dynamics and without joint torque measurementabstractIgnoring actuator dynamics in control of rigid manipulators can in practice result in performance degradation or loss of system stability. However, consideration of actuator dynamics usually requires measurement of robot joint torques. This paper addresses motion tracking control of an n-DOF rigid robot by taking into account its actuator dynamics. Joint torque measurement is avoided by using an adaptive observer. The backstepping technique is adopted to develop a dynamically smooth adaptive nonlinear controller dealing with uncertainties in manipulator and actuator dynamics. Semi-global convergence of motion tracking errors as well as torque estimation error are proven without any persistency of excitation condition. Simulation examples demonstrate low noise sensitivity of the proposed method in comparison with those using torque measurement. Yahya S. Khaligh, Mehrzad Namvar |
ICRA | 1 |