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Jianle Xu

dblp:388/0365 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2025
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021Systems, architecture and hardware · 2 · 1 first-author · 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
1 paper
Motion planning and robot control · 67% Robot manipulation · 33%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › cable-driven robot
cable-driven manipulator
0.912025
D3-ARM: High-Dynamic, Dexterous and Fully Decoupled Cable-Driven Robotic Arm · ICRA 2025
Robotics › Motion planning and robot control
motion decoupling
0.912025
D3-ARM: High-Dynamic, Dexterous and Fully Decoupled Cable-Driven Robotic Arm · ICRA 2025
Robotics › Motion planning and robot control
robot control
0.912025
D3-ARM: High-Dynamic, Dexterous and Fully Decoupled Cable-Driven Robotic Arm · ICRA 2025

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

cable-pretension mechanism · 0.9
YearPublicationVenuePosition
2025 D3-ARM: High-Dynamic, Dexterous and Fully Decoupled Cable-Driven Robotic Arm
abstract
Cable transmission enables motors of robotic arm to operate lightweight and low-inertia joints remotely in various environments, but it also creates issues with motion coupling and cable routing that can reduce arm's control precision and performance. In this paper, we present a novel motion decoupling mechanism with low-friction to align the cables and efficiently transmit the motor's power. By arranging these mechanisms at the joints, we fabricate a fully decoupled and lightweight cable-driven robotic arm called D3-Arm with all the electrical components be placed at the base. Its 776 mm length moving part boasts six degrees of freedom (DOF) and only 1.6 kg weights. To address the issue of cable slack, a cable-pretension mechanism is integrated to enhance the stability of long-distance cable transmission. Through a series of comprehensive tests, D3-Arm demonstrated 1.29 mm average positioning error and 2.0 kg payload capacity, proving the practicality of the proposed decoupling mechanisms in cable-driven robotic arm.
Jianle Xu, Shoujie Li, Huayue Liang, Yanbo Chen 0001, Chongkun Xia, Xueqian Wang 0001
ICRA2
2025 MuxHand: A Cost-Effective and Compact Dexterous Robotic Hand Using Time-Division Multiplexing Mechanism
abstract
The number of motors directly influences the dexterity, size, and cost of a robotic hand. In this paper, we present MuxHand, a robotic hand that utilizes a time-division multiplexing motor (TDMM) mechanism. This system enables independent control of 9 cables with just 4 motors, significantly reducing both cost and size while maintaining high dexterity. To enhance stability and smoothness during grasping and manipulation tasks, we integrate magnetic joints into the three 3D-printed fingers. These joints provide impact resistance, resetting capabilities. The three fingers together have a total of 30 degrees of freedom (DOF), 18 of which are passive DOF, allowing the hand to conform closely to the surface of an object during grasping. We conduct a series of experiments to assess the performance parameters of MuxHand, including its grasping and manipulation capabilities. The results show that the TDMM mechanism precisely controls each cable connected to the finger joints, enabling robust grasping and dexterous manipulation. Furthermore, compared to the traditional approach of assigning a motor to each active DOF, the cost is reduced by 42.06%. The maximum load of a single finger reaches 7.0 kg, the maximum load at the finger joint root is 12.0 kg, the maximum driving force at the joint root is 5.0 kg, and the maximum fingertip force is 10.0 N.
Jianle Xu, Shoujie Li, Houde Liu, Xueqian Wang 0001, Wenbo Ding 0001, Chongkun Xia
IROS1