2018 International Symposium on Medical Robotics (ISMR) 2018
DOI: 10.1109/ismr.2018.8333292
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Da Vinci tool torque mapping over 50,000 grasps and its implications on grip force estimation accuracy

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Cited by 12 publications
(6 citation statements)
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“…Here, the torque sensors were essential for determining slip and adjusting the grasp [ 52 ]. The ability to measure torques at the object–gripper interface enables precise grip force adjustments and opens up new uses of tactile sensors, such as being used for improving the grasping abilities, for example, in surgical tools [ 53 , 54 ] and precise positioning and applying rotation forces in assembly tasks [ 50 ].…”
Section: Discussionmentioning
confidence: 99%
“…Here, the torque sensors were essential for determining slip and adjusting the grasp [ 52 ]. The ability to measure torques at the object–gripper interface enables precise grip force adjustments and opens up new uses of tactile sensors, such as being used for improving the grasping abilities, for example, in surgical tools [ 53 , 54 ] and precise positioning and applying rotation forces in assembly tasks [ 50 ].…”
Section: Discussionmentioning
confidence: 99%
“…The training is based on a set of measurements at the beginning of the surgery that is used afterward for force estimation throughout the entire surgery. Proposed approaches that have an instrument's operational parameters as inputs, do not consider the variations between instruments and the change of instruments behavior throughout its use (Kong et al, 2018). Considering how the research direction has evolved over the past decade, experimentation with different model architectures, development of efficient training, and identification methods that can be automatically performed at the system start-up (Spiers et al, 2015), improving the computation time and incorporation of online adaptation techniques are attractive research areas to be further investigated.…”
Section: Discussionmentioning
confidence: 99%
“…In addition, any model relies on a set of measurements (calibration or training set) that are usually taken at the beginning and used throughout the estimation. It is experimentally shown that the tool behavior changes with time which deteriorates the estimation accuracy (Hadi Hosseinabadi et al, 2019;Kong et al, 2018). The environmental parameters such as temperature and humidity can also affect the instrument characteristics The severity level of the sources that contribute to the measurement inaccuracy (scale of 1 to 3; 1 is minimum, 3 is maximum, and × is no effect), and the importance of design requirements (scale of 1 to 3; 1 is the least, 3 is the most, and × refers to not a requirement) are compared.…”
mentioning
confidence: 99%
“…Position and torque data were time-synchronously collected on both ends. Details of the hardware setup including the sensors used on the proximal and distal ends are explained in [4] and [5], respectively. For this dataset, the tested range of orientations included the following: pitch angles (-60 to +60°), roll angles (-90 to +90°) and yaw angles (-90 to +30°).…”
Section: Methodsmentioning
confidence: 99%
“…The estimation technique utilized in this work is an artificial neural network similar to the one explained in [4]. The neural network architecture consisted of 60 nodes in a single hidden layer, with input features of position, velocity, torque, pitch spindle, and roll spindle all measured on the proximal end.…”
Section: Methodsmentioning
confidence: 99%