Low-Cost Fiducial-based 6-Axis Force-Torque Sensor

Ouyang, Rui; Howe, Robert D.

doi:10.1109/icra40945.2020.9196925

Cited by 12 publications

(3 citation statements)

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“…For force sensing in different surgical procedures, the flexure should also be changeable according to the task requirements. One commercial and readily available flexure is the compression spring [22], [23]. Although compression springs typically show dominant stiffness in the axial direction, they also exhibit a certain degree of stiffness in lateral directions and can be linearly approximated [36].…”

Section: Vision-based Force Sensing Modulementioning

confidence: 99%

“…For example, many researchers investigated texture sensing and shape reconstruction based on GelSight [21]. Ouyang et al [22] developed a low-cost multi-axis force sensor based on a fiducial marker supported by four compression springs. In [22], a camera was used to estimate the displacement of the marker, which was converted to force information by multiplying a linear transformation matrix.…”

Section: Introductionmentioning

confidence: 99%

“…Ouyang et al [22] developed a low-cost multi-axis force sensor based on a fiducial marker supported by four compression springs. In [22], a camera was used to estimate the displacement of the marker, which was converted to force information by multiplying a linear transformation matrix. With almost the same principle, Fernandez et al [23] also presented a vision-based force sensor for a humanoid robot's fingers.…”

Section: Introductionmentioning

confidence: 99%

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Haptics-Enabled Forceps with Multi-Modal Force Sensing: Towards Task-Autonomous Robotic Surgery

Liu¹,

Zhang²,

Katupitiya³

et al. 2023

Preprint

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Current minimally invasive surgical robots are lacking in force sensing that is robust to temperature and electromagnetic variation while being compatible with micro-sized instruments. This paper presents a multi-axis force sensing module that can be integrated with micro-sized surgical instruments such as biopsy forceps. The proposed miniature sensing module mainly consists of a flexure, a camera, and a target. The deformation of the flexure is obtained by the pose variation of the top-mounted target, which is estimated by the camera with a proposed pose estimation algorithm. Then, the external force is estimated using the flexure's displacement and stiffness matrix. Integrating the sensing module, we further develop a pair of haptics-enabled forceps and realize its multi-modal force sensing, including touching, grasping, and pulling when the forceps manipulate tissues. To minimize the unexpected sliding between the forceps' clips and the tissue, we design a micro-level actuator to drive the forceps and compensate for the motion introduced by the flexure's deformation. Finally, a series of experiments are conducted to verify the feasibility of the proposed sensing module and forceps, including an automatic robotic grasping procedure on ex-vivo tissues. The results indicate the sensing module can estimate external forces accurately, and the haptics-enabled forceps can potentially realize multi-modal force sensing for task-autonomous robotic surgery. A video demonstrating the experiments can be found at https://youtu.be/4UUTT hiFcI.

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Section: Vision-based Force Sensing Modulementioning

confidence: 99%