Demo Data from EDBT 2026 / reviewers in the wild / expert
Jin Bao
dblp:71/6807
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2011
0009-0006-0258-681XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 2 first-authorSystems, architecture and hardware · 2 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 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
motion planning |
0.1 | 1 | 2005 | Real-Time Sensor-Based Motion Planning for Robot Manipulators · ICRA 2005 |
Robotics › Motion planning and robot control › collision avoidance
sensor-based collision avoidance |
0.1 | 1 | 2005 | Real-Time Sensor-Based Motion Planning for Robot Manipulators · ICRA 2005 |
Robotics › Motion planning and robot control › motion planning
configuration space |
0.0 | 1 | 2005 | Real-Time Sensor-Based Motion Planning for Robot Manipulators · ICRA 2005 |
Methods — techniques the papers use, named apart from their topics
sensitive skin sensing · 0.1configuration space mapping · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Crowdsourcing Creativity: Generating and Combining Ideas using Crowds
Jin Bao, Yasuaki Sakamoto |
CogSci | 1 |
| 2005 | Real-Time Sensor-Based Motion Planning for Robot ManipulatorsabstractIn this paper, a sensor-based motion planning method for robot arm manipulators operating among unknown obstacles of arbitrary shape is presented. It can be applied to on-line collision avoidance with no prior knowledge of the obstacles. The sensitive skin is used to build a description of the robot’s surroundings. This approach is based on the configuration space but the construction of the C-obstacle surface is avoided. The motion planning algorithm consists of three phases. In each phase, the point automation moves along a specified plane, on which the mapping of the obstacles into configuration space can be simplified. Hence, the computation time is reduced and the algorithm can work in real time. The effectiveness of the proposed method is verified by a series of simulations. Yili Fu 0001, Jin Bao, Shuguo Wang, Zhengcai Cao |
ICRA | 2 |
| 2005 | Sensor-based motion planning for robot manipulators in unknown environmentsabstractThis paper deals with sensor-based motion planning method for a robot arm manipulator operating among unknown obstacles of arbitrary shape. It can be applied to online collision avoidance with no prior knowledge of the obstacles. The sensitive skin is used to build a description of the robot's surroundings. This approach is based on the configuration space but the construction of the C-obstacle surface is avoided. The point automation is confined on some planes with square grids in the C-space. A path searching algorithm based on the square grids is used to guide the automation maneuvering around the C-obstacles on the selected planes. To avoid the construction of the C-obstacle surface, the robot geometry model is expanded, and the static collision detection method is used. Hence, the computation time is reduced and the algorithm can work in real time. The effectiveness of the proposed method is verified by a series of simulations. Jin Bao, Shuguo Wang, Yili Fu 0001 |
IROS | 1 |