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Hongji Shang

dblp:287/4783 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 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
1 paper
Robot manipulation · 44% 3D vision · 44% Motion planning and robot control · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
3d shape reconstruction
0.612022
Orientation to Pose: Continuum Robots Shape Reconstruction Based on the Multi-Attitude Solving Approach · ICRA 2022
Robotics › Robot manipulation
continuum robot
0.612022
Orientation to Pose: Continuum Robots Shape Reconstruction Based on the Multi-Attitude Solving Approach · ICRA 2022
Robotics › Motion planning and robot control › robot kinematics
continuum robot kinematics
0.212022
Orientation to Pose: Continuum Robots Shape Reconstruction Based on the Multi-Attitude Solving Approach · ICRA 2022

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

piecewise polynomial curvature kinematics · 0.6IMU sensor fusion · 0.6
YearPublicationVenuePosition
2022 Orientation to Pose: Continuum Robots Shape Reconstruction Based on the Multi-Attitude Solving Approach
abstract
Continuum robots are typically slender and flexible with infinite freedoms in theory, which poses a challenge for their control and application. The shape reconstruction of continuum robots is vital to realize closed-loop control. This paper proposes a novel general real-time shape reconstruction framework of continuum robots based on the piecewise polynomial curvature (PPC) kinematics model. We illustrate the coupling between orientation and position at any given location of the continuum robots. Further, the coupling relation could be bridged by the PPC kinematics. Therefore, we propose to estimate the shape through multi-attitude solving, using the off-the-shelf orientation sensors, e.g., IMUs, mounted on certain locations. The approach gives a valuable framework to real-time shape reconstruction of continuum robots, which is general, accurate and convenient. The accuracy of our approach is verified in the experiments of distinct physical prototypes.
Hejie Xu, Hongji Shang, Xueqian Wang 0001, Houde Liu, Bin Liang 0001
ICRA3