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Guochao Bai

dblp:182/9221 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 2 since 2021Systems, architecture and hardware · 2 · 2 since 2021

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 manipulation · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › robotic hand
underactuated hand
0.722023
Mechanical Intelligence for Adaptive Precision Grasp · ICRA 2021
Mechanical Intelligence for Prehensile In-Hand Manipulation of Spatial Trajectories · ICRA 2023
Robotics › Robot manipulation
dexterous manipulation
0.712023
Mechanical Intelligence for Prehensile In-Hand Manipulation of Spatial Trajectories · ICRA 2023
Robotics › Robot manipulation › dexterous manipulation
in-hand manipulation
0.712023
Mechanical Intelligence for Prehensile In-Hand Manipulation of Spatial Trajectories · ICRA 2023
Robotics › Robot manipulation › grasping
precision grasping
0.512021
Mechanical Intelligence for Adaptive Precision Grasp · ICRA 2021
Robotics › Robot manipulation › grasping › multifingered grasping
power grasp
0.112021
Mechanical Intelligence for Adaptive Precision Grasp · ICRA 2021

Methods — techniques the papers use, named apart from their topics

mechanical intelligence · 1.2open-loop control · 0.7under-actuation · 0.5
YearPublicationVenuePosition
2023 Mechanical Intelligence for Prehensile In-Hand Manipulation of Spatial Trajectories
abstract
The application of mechanical and other physical properties to the development of robotic systems that can easily adapt to changing external situations is known as mechanical intelligence. Following this concept, many robot hand designs can produce self-adaptive and versatile grasps with simple underactuated fingers and open-loop control, while mechanical- intelligent strategies for dexterous manipulation are still limited. This paper proposes a mechanical-intelligent technique to facilitate dexterous manipulation, in particular prehensile inhand manipulation. The proposed strategy is based on the generation of complex spatial trajectories of the hand-object system, controlled in open loop with the minimum number of actuators and using simple low-level non-position modes. This approach is exemplified by the rigorous analysis and testing of a three-fingered two-actuator underactuated robot hand, called the helical hand, which is capable of generating helical prehensile in-hand manipulation of diversiform objects under error tolerance controlled by constant speed algorithm.
Qiujie Lu, Zhongxue Gan 0001, Guochao Bai, Nicolás Rojas 0002
ICRA4
2021 Mechanical Intelligence for Adaptive Precision Grasp
abstract
Mechanical intelligence is the use of mechanical and other physical properties to create robotic systems adaptable to new external situations using simple control schemes. Designs of robot hands have successfully been developed and optimised following this principle to produce self-adaptive and versatile power grasps via implementations based on underactuated fingers, elastic components, and open-loop motor control. However, these characteristics, and mechanical-intelligent strategies in general, have been seldom leveraged for precision grasping. This paper proposes a mechanical-intelligent technique to facilitate not only spiral caging power grasp, but also self-adaptive precision grasp with error tolerance. This approach is exemplified by the rigorous analysis, development, and testing of a novel three-fingered, two-actuator, underactuated robot hand, called the helical hand, which is capable of self-adaptive precision grasping, and of generating spiral helical power grasps of unknown objects by simply setting two actuators at a constant speed.
Qiujie Lu, Nicholas Baron, Guochao Bai, Nicolás Rojas 0002
ICRA3