Towards Robotised Palpation for Cancer Detection through Online Tissue Viscoelastic Characterisation with a Collaborative Robotic Arm
arxiv(2024)
摘要
This paper introduces a new method for estimating the penetration of the end
effector and the parameters of a soft body using a collaborative robotic arm.
This is possible using the dimensionality reduction method that simplifies the
Hunt-Crossley model. The parameters can be found without a force sensor thanks
to the information of the robotic arm controller. To achieve an online
estimation, an extended Kalman filter is employed, which embeds the contact
dynamic model. The algorithm is tested with various types of silicone,
including samples with hard intrusions to simulate cancerous cells within a
soft tissue. The results indicate that this technique can accurately determine
the parameters and estimate the penetration of the end effector into the soft
body. These promising preliminary results demonstrate the potential for robots
to serve as an effective tool for early-stage cancer diagnostics.
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