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Joint-level force sensing for indirect hybrid force/position control of continuum robots with friction
The International Journal of Robotics Research ( IF 7.5 ) Pub Date : 2020-12-29 , DOI: 10.1177/0278364920979721
Rashid Yasin 1 , Nabil Simaan 1
Affiliation  

Continuum robots offer the dexterity and obstacle circumvention capabilities necessary to enable surgery in deep surgical sites. They also can enable joint-level ex situ force sensing (JEFS), which provides an estimate of end-effector wrenches given joint-level forces. Prior works on JEFS relied on a restrictive embodiment with minimal actuation line friction and captured model and frictional actuation transmission uncertainties using a configuration space formulation. In this work, we overcome these limitations. First, frictional losses are canceled using a feed-forward term based on support vector regression in joint space. Then, regression maps and their interpolation are used to account for actuation hysteresis. The residual joint-force error is then further minimized using a least-squares model parameter update. An indirect hybrid force/position controller using JEFS is presented with evaluation carried out on a realistic pre-clinically deployable insertable robotic effectors platform (IREP) for single-port access surgery. Automated mock force-controlled ablation, exploration, and knot tightening are evaluated. A user study involving the daVinci Research Kit surgeon console and the IREP as a surgical slave was carried out to compare the performance of users with and without force feedback based on JEFS for force-controlled ablation and knot tightening. Results in automated experiments and a user study of telemanipulated experiments suggest that intrinsic force-sensing can achieve levels of force uncertainty and force regulation errors of the order of 0.2 N. Using JEFS and automated task execution, repeatability, and force regulation accuracy is shown to be comparable to using a commercial force sensor for human-in-the-loop feedback.



中文翻译:

关节级力感测用于具有摩擦的连续机器人间接混合力/位置控制

连续机器人提供了在深部手术部位进行手术所必需的敏捷性和障碍物规避能力。它们还可以实现异地联合级别力感测(JEFS),在给定关节水平力的情况下,它可以估算末端执行器扳手。JEFS的先前工作依赖于限制性实施例,该致动器具有最小的致动线摩擦力,并且使用配置空间公式来捕获模型和摩擦致动传递不确定性。在这项工作中,我们克服了这些限制。首先,使用基于关节空间中支持向量回归的前馈项消除摩擦损失。然后,使用回归图及其内插法来考虑致动滞后。然后,使用最小二乘模型参数更新将残余的关节力误差进一步最小化。提出了使用JEFS的间接混合力/位置控制器,并在实际的临床前可部署的可插入式机器人效应器平台(IREP)上进行了评估,以用于单端口进入手术。评估了自动模拟力控制的消融,探查和结紧的情况。进行了一项涉及daVinci Research Kit外科医生控制台和IREP作为外科手术奴隶的用户研究,以比较基于JEFS进行力控制消融和结节收紧的有无力反馈的用户的性能。自动化实验和用户对远程操纵实验的研究结果表明,固有的力感测可以实现0.2 N量级的力不确定性和力调节误差。使用JEFS和自动任务执行,可重复性,

更新日期:2020-12-29
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