Spatial motion constraints for a minimally invasive surgical robot using customizable virtual fixtures

Tang, Aolin; Cao, Qixin; Pan, Tiewen

doi:10.1002/rcs.1551

Cited by 10 publications

(9 citation statements)

References 31 publications

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“…The introduction of VFs, especially interactive ones, improved teleoperation performance in our previous work (Pruks and Ryu 2020) and related studies (Lee and Park 2018;Quintero et al, 2017;Selvaggio et al, 2018;Tang et al, 2013;Vagvolgyi et al, 2018). However, there have been none that compared different interactive VF generation methods.…”

Section: Experimental Studymentioning

confidence: 95%

“…The O and L methods used the proposed interface, and the Q method used the original interface. The L methods used different human inputs: Tang et al (2013); Selvaggio et al (2018) recorded RR positions; Lee and Park (2018) recorded HI positions in the AR; Vagvolgyi et al (2018) recorded points selected with computer mouse. To save time on the development of the special interface for the L method, it was decided to replicate the human interaction in our proposed UI.…”

Section: Methodsmentioning

confidence: 99%

“…Tang’s (Tang et al, 2013), Quintero’s (Quintero et al, 2017), Selvaggio’s (Selvaggio et al, 2018), Lee’s (Lee and Park 2018), and Vagvolgyi’s (Vagvolgyi et al, 2018) works demonstrated the feasibility of user-interactive VF generation. However, these methods suffer from several limitations.…”

Section: Introductionmentioning

confidence: 99%

“…A few works have studied such interactive VF generation methods. Tang et al (2013) proposed a method of generating a forbidden-region VF by recording the trajectory of the RR moving in free space. Through this method, the forbidden regions obtained arbitrary 3D surface shapes.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, this paper compares the performance of the proposed method with two groups of interactive VF generation methods. The first group comprises methods of generating VFs without orientation feedback (Lee and Park 2018; Selvaggio et al, 2018; Tang et al, 2013; Vagvolgyi et al, 2018). The second group comprises a single method that generates VFs with both translation and orientation feedback (Quintero et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Method for generating real-time interactive virtual fixture for shared teleoperation in unknown environments

Pruks¹,

Ryu

2022

The International Journal of Robotics Research

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A virtual fixture (VF) is a constraint built into software that assists a human operator in moving a remote tool along a preferred path via an augmented guidance force to improve teleoperation performance. However, teleoperation generally applies to unknown or dynamic environments, which are challenging for VF use. Most researchers have assumed that VFs are pre-defined or generated automatically; however, these processes are complicated and unreliable in unknown environments where teleoperation is in high demand. Recently, a few researchers have addressed this issue by introducing a user-interactive method of generating VFs in unknown environments. However, these methods are limited to generating a single type of primitive for a single robot tool. Moreover, the accuracy of the VF generated by these methods depends on the accuracy of the human input. Thus, applications of these methods are limited. To overcome those limitations, this work introduces a novel interactive VF generation method that includes a new method of representing VFs as a composition of components. A feature-based user interface allows the human operator to intuitively specify the VF components. The new VF representation accommodates a variety of robot tools and actions. Using the feature-based interface, the process of VF generation is more intuitive and accurate. In this study, the proposed method is evaluated with human subjects in three teleoperation experiments: peg-in-hole, pipe-sawing, and pipe-welding. The experimental results show that the VFs generated by the proposed approach result in a higher manipulation quality while demonstrating the lowest total workload in all experiments. The peg-in-hole task teleoperation was the safest in terms of failure proportion and exerted force of the robot tool. In the pipe-sawing task, the positioning of the robot tool was the most accurate. In the pipe-welding task, the quality of weld was the best in terms of measured tool-trajectory smoothness and visual weld observation.

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