Demo Data from VLDB 2026 / reviewers in the wild / expert
William Howell
dblp:49/793
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4Systems, architecture and hardware · 3
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 |
Robot navigation and mapping · 33% Motion planning and robot control · 26% Planning, search and constraint satisfaction · 26% |
Topics — the 6 heaviest of 6, 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 |
0.1 | 1 | 2008 | Hierarchical two stage planner for little dog · ICRA 2008 |
Robotics › Motion planning and robot control
motion planning |
0.1 | 1 | 2008 | Hierarchical two stage planner for little dog · ICRA 2008 |
Robotics › Robot navigation and mapping › robot mapping
terrain mapping |
0.1 | 1 | 2008 | Learning terrain cost maps · ICRA 2008 |
Robotics › Legged, aerial and field robots
field robotics |
0.0 | 1 | 2008 | Learning terrain cost maps · ICRA 2008 |
Robotics › Legged, aerial and field robots
legged robots |
0.0 | 1 | 2008 | Hierarchical two stage planner for little dog · ICRA 2008 |
Robotics › Robot navigation and mapping › mobile robot navigation › terrain-aware navigation
rough terrain navigation |
0.0 | 1 | 2008 | Learning terrain cost maps · ICRA 2008 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | The Yobotics-IHMC Lower Body Humanoid RobotabstractThis video highlights work to date on the Yobotics-IHMC lower body humanoid robot. The robot is a twelve degree-of-freedom robot with force controllable series elastic actuators at each degree of freedom. Control algorithms utilize virtual model control, and foot placement is determined using capture regions. The robot can recover from moderate disturbances and walk on flat ground. Ongoing work is focused on improving robustness to disturbances, walking more quickly and efficiently, and walking over rough terrain. Jerry E. Pratt, Benjamin T. Krupp, Victor Ragusila, John R. Rebula, Twan Koolen, Niels van Nieuwenhuizen, Christopher Shake, Travis Craig, Greg Watkins, Peter D. Neuhaus, Matt Johnson 0001, Steve Shooter, Keith W. Buffinton, Fabian Canas, John Carff, William Howell |
IROS | 17 |
| 2008 | Hierarchical two stage planner for little dog
Brian V. Bonnlander, John R. Rebula, Peter D. Neuhaus, Matt Johnson 0001, Greg Hill, Carlos Pérez, John Carff, William Howell, Jerry E. Pratt |
ICRA | 8 |
| 2008 | Learning terrain cost maps
John R. Rebula, Greg Hill, Brian V. Bonnlander, Matt Johnson 0001, Peter D. Neuhaus, Carlos Pérez, John Carff, William Howell, Jerry E. Pratt |
ICRA | 8 |
| 2005 | Welcome to the special issue
Danil V. Prokhorov, Daniel S. Levine 0001, Fredric M. Ham, William Howell |
Neural Networks | 4 |