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Ran Xu 0010

dblp:71/1270-10 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2017
0009-0007-7847-8070ORCID · 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 · 3 · 2 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
2 papers
Motion planning and robot control · 71% Robot manipulation · 29%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › flexible robot control
continuum robot control
0.422014
Real-time trajectory tracking for externally loaded concentric-tube robots · ICRA 2014
Position control of concentric-tube continuum robots using a modified Jacobian-based approach · ICRA 2013

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

force sensing · 0.2dual-layer control · 0.2torsionally compliant kinematic model · 0.2
YearPublicationVenuePosition
2017 Development of an optical fiber-based sensor for grasping and axial force sensing
abstract
In spite of the remarkable benefits that minimally invasive surgery provides for patients, the absence of force feedback is still a significant disadvantage. Several studies have been performed to address this issue; however, an accurate sterilizable force sensing technology for measuring axial and grasping forces is still missing. In this work, an innovative partial grasper has been designed and developed for a laparoscopic needle driver that can measure axial and grasping force information at the grasper tip. Fiber Bragg Grating sensors are used in this work because of their sterilizability and high sensitivity. Accuracies of 0.19 N and 0.26 N were achieved for the grasping and axial sensors respectively.
Pouya Soltani Zarrin, Abelardo Escoto, Ran Xu 0010, Rajnikant V. Patel, Michael D. Naish, Ana Luisa Trejos
ICRA3
2014 Real-time trajectory tracking for externally loaded concentric-tube robots
abstract
Concentric-tube robots can offer a suitable compromise between force and curvature control. In a previous study by the authors, a real-time trajectory tracking scheme for an unloaded concentric-tube robot was developed. One of the practical barriers to the use of a concentric-tube robot in medical applications is compensation for the impact of environmental forces which can cause drastic deterioration in tracking performance. In this paper, by modifying the robot's forward kinematics and Jacobian, a new method is developed to facilitate tip tracking in real-time while accounting for an external load at the robot's tip. By considering the tip deflection resulting from the external load, a novel dual-layer control architecture is proposed to compensate for this deflection during trajectory tracking. In order to measure the force exerted on the tip position of the robot, a new technique is proposed that can move the sensing system from the distal tip to the proximal base. Experimental results are given to illustrate the effectiveness of the proposed method.
Ran Xu 0010, Ali Asadian, Seyed Farokh Atashzar, Rajnikant V. Patel
ICRA1
2013 Position control of concentric-tube continuum robots using a modified Jacobian-based approach
abstract
Concentric-tube robots can offer dexterous positioning even in a small constrained environment. This technology turns out to be beneficial in many classes of minimally invasive procedures. However, one of the barriers to the practical use of a concentric-tube robot is the design of a real-time control scheme. In previous work by the authors, a computationally efficient torsionally compliant kinematic model of a concentric-tube robot was developed. Using this computationally fast technique and deriving the robot's Jacobian, a new position control approach is proposed in this paper. This mechanism provides computational efficiency as well as good tracking accuracy. To evaluate the performance, experiments were conducted, and the results obtained demonstrate the feasibility of enabling the robot's tip to perform trajectory tracking in real time.
Ran Xu 0010, Ali Asadian, Anish S. Naidu, Rajnikant V. Patel
ICRA1