ArticleIEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation2016
Dynamic Modeling of Cable Driven Elongated Surgical Instruments for Sensorless Grip Force Estimation.
Article in IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Deformable and Fragile Object Manipulation: A Review and Prospects.Sensors (Basel, Switzerland) · 2025Review
- Advancements and challenges in robotic surgery: A holistic examination of operational dynamics and future directions.Surgery in practice and science · 2025Review
- Transfer of learned dynamics between different surgical robots and operative configurations.International journal of computer assisted radiology and surgery · 2022Article
- Pneumatically driven surgical forceps displaying a magnified grasping torque.The international journal of medical robotics + computer assisted surgery : MRCAS · 2020Article
- Conditions for reliable grip force and jaw angle estimation of da Vinci surgical tools.International journal of computer assisted radiology and surgery · 2019Article
- Cable-Driven Parallel Robot with Reconfigurable End Effector Controlled with a Compliant Actuator.Sensors (Basel, Switzerland) · 2018Article
- Efficiency and Power Limits of Electrical and Tendon-Sheath Transmissions for Surgical Robotics.Frontiers in robotics and AI · 2018Article
- Gaussian Process Regression for Sensorless Grip Force Estimation of Cable Driven Elongated Surgical Instruments.IEEE robotics and automation letters · 2017Article
- Dynamic Modeling of Cable Driven Elongated Surgical Instruments for Sensorless Grip Force Estimation.IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation · 2016Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Haptic feedback plays a key role in surgeries, but it is still a missing component in robotic Minimally Invasive Surgeries. This paper proposes a dynamic model-based sensorless grip force estimation method to address the haptic perception problem for commonly used elongated cable-driven surgical instruments. Cable and cable-pulley properties are studied for dynamic modeling; grip forces, along with driven motor and gripper jaw positions and velocities are jointly estimated with Unscented Kalman Filter and only motor encoder readings and motor output torques are assumed to be known. A bounding filter is used to compensate for model inaccuracy and to improve method robustness. The proposed method was validated on a 10mm gripper which is driven by a Raven-II surgical robot. The gripper was equipped with 1-dimensional force sensors which served as ground truth data. The experimental results showed that the proposed method provides sufficiently good grip force estimation, while only motor encoder and the motor torques are used as observations.
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Registered trials
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