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Runfeng Zhu

dblp:383/4510 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2024
0009-0006-8333-1762ORCID · reported

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
2 papers
Robot manipulation · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › medical robotics
surgical robotics
1.522024
Design and Implementation of A Robotized Hand-held Dissector for Endoscopic Pulmonary Endarterectomy · ICRA 2024
Co-Axial Slender Tubular robot (CAST): Towards Robotized Operation for Transorbital Neurosurgery with Minimal Invasiveness · ICRA 2024
Robotics › Robot manipulation › continuum robot
tendon-driven continuum robot
0.212024
Co-Axial Slender Tubular robot (CAST): Towards Robotized Operation for Transorbital Neurosurgery with Minimal Invasiveness · ICRA 2024

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

tendon-mortise slit design · 0.8stiffness regulation · 0.8force estimation · 0.8cable-driven actuation · 0.8
YearPublicationVenuePosition
2024 Co-Axial Slender Tubular robot (CAST): Towards Robotized Operation for Transorbital Neurosurgery with Minimal Invasiveness
abstract
Transorbital Neuro Surgery (TNS) offers a novel treatment towards the lesion inside skull pursuing minimal invasiveness. Most conventional TNS tools are rigid and straight, limiting the dexterity and accessibility in passing a small port. Bendable and steerable surgical tools provides an alternative for this issue. In this work, we proposed a dual-segment slender surgical robot arm for TNS, which is a Co-Axial Slender Tubular robot (CAST), and modelled it using novel approaches. Another contribution is tendon-mortise shaped slits along the axial direction, enhancing the overall stiffness. The bending of CAST is actuated by pushing/pulling distance, and the maximum diameter is only 1.7mm with high dexterity after mounting on a rigid robot arm. Experiments demonstrates that the proposed the slit design doubles the stiffness properties compared to traditional rectangle slit designs. The path-following task shows that the position error was maximally 3mm in open-looped control. Test on a skull model demonstrates that the whole system could successfully perform electrocoagulation procedure inside the depth of skull in a robotized manner effectively.
Shuai Wang 0024, Qingxiang Zhao, Jian Chen 0036, Mingcong Chen, Guanglin Cao, Runfeng Zhu, Danny Tat-Ming Chan, Ming Feng, Hongbin Liu 0001
ICRA7
2024 Design and Implementation of A Robotized Hand-held Dissector for Endoscopic Pulmonary Endarterectomy
abstract
Severe chronic pulmonary endarterectomy needs a dissector to delicately remove proliferative intima located in the depth of the pulmonary artery. This work proposed a novel endoscopic robotized steerable dissector for this surgery, enabling easier access to curved deep artery branches. The handheld surgical dissector also provides suction and visualization for surgeons to enhance effectiveness. The steerable section is a cable-driven hinged structure, and through an antagonistic mechanism regulating the cable tension, the overall stiffness is adjusted to adapt various surroundings. The mapping between actuation space and shape configuration and tip force estimation model are respectively established for further closed-loop control scheme, achieving adaptive positioning and safe surgery. Experiments first demonstrate the feasibility of the proposed models and ex vitro trials validated the usage and effectiveness of the robotized dissector.
Runfeng Zhu, Xilong Hou 0001, Hongbin Liu 0001, Henry K. Chu, Qingxiang Zhao
ICRA1