Demo Data from VLDB 2026 / reviewers in the wild / expert
David Chiu 0002
dblp:64/411-2
· DBLP profile ↗
5ranked-venue papers
3as first author
0since 2021 · last 1997
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 5 · 3 first-authorSystems, architecture and hardware · 5 · 3 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
2 papers |
Motion planning and robot control · 91% Robot manipulation · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control
force control |
0.0 | 2 | 1997 | Gain scheduling and integral action in manipulator collision control · ICRA 1997 Design and experimentation of jump impact controller · ICRA 1996 |
Robotics › Motion planning and robot control › robot control › force control
impact control |
0.0 | 2 | 1997 | Gain scheduling and integral action in manipulator collision control · ICRA 1997 Design and experimentation of jump impact controller · ICRA 1996 |
Robotics › Motion planning and robot control
manipulator control |
0.0 | 2 | 1997 | Gain scheduling and integral action in manipulator collision control · ICRA 1997 Design and experimentation of jump impact controller · ICRA 1996 |
Robotics › Robot manipulation › contact modeling
collision dynamics |
0.0 | 2 | 1997 | Gain scheduling and integral action in manipulator collision control · ICRA 1997 Design and experimentation of jump impact controller · ICRA 1996 |
Methods — techniques the papers use, named apart from their topics
observer design · 0.0integral action · 0.0gain scheduling · 0.0stochastic process modeling · 0.0jump linear system · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | Gain scheduling and integral action in manipulator collision controlabstractIn this paper, jump impact controller and observer derived previously for the manipulator collision control problem under the conditions that there are force sensor delay and uncertainties in the environment dynamics and location is modified with better intuitive appeal and understanding. It turns out that the solution is a combination of integral action and gain scheduling which provide a valuable design freedom or tool to achieve the desired robustness and performance in accordance with the uncertainties involved. An example that demonstrate this design process with simulation results are presented. David Chiu 0002, Sukhan Lee 0001 |
ICRA | 1 |
| 1996 | Design and experimentation of jump impact controllerabstractA new impact/force controller known as jump impact controller (JIC) is designed and evaluated experimentally. JIC is derived by representing dynamics of collision in terms of a jump linear system where the jumps of system dynamics can be described by a state-dependent stochastic process. Thus, JIC provides robustness to the uncertainties in the environment dynamics as well as the location of the collision surface. The experimental results not only verify the robustness of JIC but also help explain and interpret how robustness is associated with the JIC theory in terms of such known concepts as approach velocity and control system bandwidth. David Chiu 0002, Sukhan Lee 0001 |
ICRA | 1 |
| 1996 | Performance robustness of manipulator collision controllerabstractWe propose that the manipulator impact control problem be approached from a stochastic optimal control perspective. The reason is that not only is such an approach able to model uncertainties in contact environment, force sensing, as well as manipulator dynamics, the controller obtained is optimally robust in terms of performance. This result is verified by analyses and simulations. Sukhan Lee 0001, David Chiu 0002 |
IROS | 2 |
| 1995 | Robust jump impact controller for manipulatorsabstractThis paper presents a novel impact controller which is robust to the uncertainties in environment dynamics and location of the collision surface. By modeling the impact dynamics as a state dependent jump linear system and applying a modified version of the stochastic maximum principle of a state dependent jump linear system, the controller thus obtained optimizes, in the mean square sense, the approach velocity, the force transient during impact and the steady state force error after contact is established. Compared with impedance controllers via simulation whose data is obtained from experimental data the results indicate that not only is the performance of the jump impact controller superior in terms of overshoot and steady state error its robustness is quite remarkable too. David Chiu 0002, Sukhan Lee 0001 |
IROS (1) | 1 |
| 1993 | Size vs. power-to-weight ratio in integrated actuationabstractInvestigates whether there exists some universal trend such that an actuator utilizing the same kind of energy source but having a small size will have an intrinsic advantage in terms of power-to-weight ratio (PWR). The results indicate that this trend does not exist in general. In fact it is found that the maximum PWR of most electric motors is independent of motor size even though their force-to-weight ratio (FWR) may vary, except that the PWR of striated muscles of vertebrates increases with muscle size. Therefore, the advantage of integrated actuation must come from other aspects such as flexibility in controlling shape, velocity and force, robustness, etc. Sukhan Lee 0001, David Chiu 0002, Kwan Tjia |
IROS | 2 |