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Jin Bao

dblp:71/6807 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
motion planning
0.112005
Real-Time Sensor-Based Motion Planning for Robot Manipulators · ICRA 2005
Robotics › Motion planning and robot control › collision avoidance
sensor-based collision avoidance
0.112005
Real-Time Sensor-Based Motion Planning for Robot Manipulators · ICRA 2005
Robotics › Motion planning and robot control › motion planning
configuration space
0.012005
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
YearPublicationVenuePosition
2011 Crowdsourcing Creativity: Generating and Combining Ideas using Crowds
Jin Bao, Yasuaki Sakamoto
CogSci1
2005 Real-Time Sensor-Based Motion Planning for Robot Manipulators
abstract
In 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
ICRA2
2005 Sensor-based motion planning for robot manipulators in unknown environments
abstract
This 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
IROS1