Demo Data from SIGIR 2026 / reviewers in the wild / expert
Philip J. Knoghtbridge
dblp:86/3309
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1995
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1
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 |
Planning, search and constraint satisfaction · 61% Reinforcement learning · 30% Motion planning and robot control · 9% |
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
hierarchical planning |
0.0 | 1 | 1995 | Task Planning and World Modelling for Supervisory Control of Robots in unstructured Environments · ICRA 1995 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
task planning |
0.0 | 1 | 1995 | Task Planning and World Modelling for Supervisory Control of Robots in unstructured Environments · ICRA 1995 |
Machine learning › Reinforcement learning › model-based reinforcement learning
world model |
0.0 | 1 | 1995 | Task Planning and World Modelling for Supervisory Control of Robots in unstructured Environments · ICRA 1995 |
Robotics › Motion planning and robot control › robot control › hierarchical control
supervisory control |
0.0 | 1 | 1995 | Task Planning and World Modelling for Supervisory Control of Robots in unstructured Environments · ICRA 1995 |
Methods — techniques the papers use, named apart from their topics
sensor fusion · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | Task Planning and World Modelling for Supervisory Control of Robots in unstructured EnvironmentsabstractWe describe the design of a task planning and world modelling mechanism as part of a supervisory or teleassistance control scheme for robots operating in unstructured environments. The mechanism addresses the key difficulties of an unstructured environment which lead to failures in task execution. Reactivity is achieved by mixing planning and execution. Complexity of task and error recovery is managed by hierarchical design of action sequences. The world model and task planner are intimately linked to allow parameterization of actions, and for the operator to focus on involved objects in the world. They work as part of a functional architecture with motion planning, dynamic control and sensor fusion processes, and have been implemented to specify the activity of a pair of underwater manipulators, sensed using force/torque loadcell, joint potentiometers, high frequency sonar and laser striping. David M. Lane, Philip J. Knoghtbridge |
ICRA | 2 |