Demo Data from VLDB 2026 / reviewers in the wild / expert
Christopher Cocca
dblp:29/5178
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1999
—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 · 50% Planning, search and constraint satisfaction · 25% Robot manipulation · 25% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › plan execution
failure recovery |
0.0 | 1 | 1999 | Failure Recovery in Redundant Serial Manipulators Using Nonlinear Programming · ICRA 1999 |
Robotics › Robot manipulation
redundant manipulator |
0.0 | 1 | 1999 | Failure Recovery in Redundant Serial Manipulators Using Nonlinear Programming · ICRA 1999 |
Robotics › Motion planning and robot control
robot control |
0.0 | 1 | 1999 | Failure Recovery in Redundant Serial Manipulators Using Nonlinear Programming · ICRA 1999 |
Robotics › Motion planning and robot control › robot control › torque control
torque-limited control |
0.0 | 1 | 1999 | Failure Recovery in Redundant Serial Manipulators Using Nonlinear Programming · ICRA 1999 |
Methods — techniques the papers use, named apart from their topics
performance criteria optimization · 0.0nonlinear programming · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1999 | Failure Recovery in Redundant Serial Manipulators Using Nonlinear ProgrammingabstractThis paper presents a simulation and analysis of partial failure recovery using nonlinear programming techniques. Previous techniques have shown partial failure recoveries that were limited by their use of a single criterion. The technique shown maintains the torque constraints imposed by the failure while minimizing additional performance criteria. One advantage of this technique is that it allows the robot to avoid parametric and mathematical limits by means of imposing additional performance criteria. Christopher Cocca, Daniel J. Cox, Delbert Tesar |
ICRA | 1 |