A vessel contour detection and estimation method for robot assisted endovascular surgery

The technique of tracking a non-cooperative manoeuvring satellite is important for Space Situation Awareness (SSA). However, the classical extended Kalman filter cannot work successfully in this situation. Motivated by this problem, a novel Extended Kalman Filter with Input Detection and Estimation (EKF/IDE) method is proposed in this paper for tracking a non-cooperative satellite with impulsive manoeuvres. The impulsive manoeuvre is modelled as an unknown acceleration without any prior information. An unbiased minimum-variance input and state estimation method is introduced to estimate the manoeuvre acceleration. An approach based on the Mahalanobis distance of the manoeuvre estimate error is proposed for manoeuvre detection. With the impulsive manoeuvre being detected and estimated accurately, an adaptive extended Kalman filter is proposed to estimate the state of the target. An approach of covariance inflation is proposed to deal with the manoeuvre during the unobserved period. Simulations and Monte Carlo experiments are implemented to demonstrate the feasibility and validity of the proposed method. The results of simulations show that the proposed method can accurately detect and estimate unknown impulsive manoeuvres of a non-cooperative satellite. Through the compensation of the estimated manoeuvre, the estimation of position and velocity after the manoeuvre maintains the accuracy of the pre-manoeuvre period, demonstrating the robustness of the proposed method against unknown manoeuvres.

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Radon-Linear Canonical Ambiguity Function-Based Detection and Estimation Method for Marine Target With Micromotion

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2014.2358456 ◽

2015 ◽

Vol 53 (4) ◽

pp. 2225-2240 ◽

Cited By ~ 46

Author(s):

Xiaolong Chen ◽

Jian Guan ◽

Yong Huang ◽

Ningbo Liu ◽

You He

Keyword(s):

Estimation Method ◽

Ambiguity Function ◽

Detection And Estimation

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Estimating Tool–Tissue Forces Using a 3-Degree-of-Freedom Robotic Surgical Tool

Journal of Mechanisms and Robotics ◽

10.1115/1.4032591 ◽

2016 ◽

Vol 8 (5) ◽

Cited By ~ 13

Author(s):

Baoliang Zhao ◽

Carl A. Nelson

Keyword(s):

Force Feedback ◽

Estimation Method ◽

Interaction Force ◽

Normal Function ◽

Degree Of Freedom ◽

Force Estimation ◽

Robot Assisted ◽

Interaction Forces ◽

Tissue Interaction ◽

Surgical Tool

Robot-assisted minimally invasive surgery (MIS) has gained popularity due to its high dexterity and reduced invasiveness to the patient; however, due to the loss of direct touch of the surgical site, surgeons may be prone to exert larger forces and cause tissue damage. To quantify tool–tissue interaction forces, researchers have tried to attach different kinds of sensors on the surgical tools. This sensor attachment generally makes the tools bulky and/or unduly expensive and may hinder the normal function of the tools; it is also unlikely that these sensors can survive harsh sterilization processes. This paper investigates an alternative method by estimating tool–tissue interaction forces using driving motors' current, and validates this sensorless force estimation method on a 3-degree-of-freedom (DOF) robotic surgical grasper prototype. The results show that the performance of this method is acceptable with regard to latency and accuracy. With this tool–tissue interaction force estimation method, it is possible to implement force feedback on existing robotic surgical systems without any sensors. This may allow a haptic surgical robot which is compatible with existing sterilization methods and surgical procedures, so that the surgeon can obtain tool–tissue interaction forces in real time, thereby increasing surgical efficiency and safety.

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