Environmental force estimation for a robotic hand: Compliant contact detection

Kaya, Osman; Yildirim, Mehmet C.; Kuzuluk, Nisan; Çiçek, Emre; Bebek, Özkan; Öztop, Erhan; Uğurlu, Barkan

doi:10.1109/humanoids.2015.7363444

Cited by 4 publications

(3 citation statements)

References 23 publications

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“…Visual servo control [36] is a promising alternative for manipulation but does not provide a complete perception of interaction force. To avoid the use of sensors, different methods have been proposed to estimate the interaction force/torque, e.g., extended Kalman filters [37][38][39][40][41], adaptive Kalman filters [42], extended state observers [43][44][45][46][47][48][49][50], disturbance observers [51,52], nonlinear observers [53], deep neural networks [54], model-based compensation techniques [55,56], task-oriented models based on dynamic model learning and a robust disturbance state observer [57], a sensorless force estimation method using a disturbance observer and the neural learning of friction [58], and extended Kalman filters [59].…”

Section: Interaction Force/torque Sensorless Estimationmentioning

confidence: 99%

Hybrid Adaptive Impedance and Admittance Control Based on the Sensorless Estimation of Interaction Joint Torque for Exoskeletons: A Case Study of an Upper Limb Rehabilitation Robot

Abdullahi,

Haruna,

Chaichaowarat

2024

JSAN

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Physiotherapy is the treatment to recover a patient’s mobility and limb function after an injury, illness, or disability. Rehabilitation robots can be used to replace human physiotherapists. To ensure safety during robot physical therapy, the patient’s limb needs to be controlled to track a desired joint trajectory, and the torque due to interaction force/torque needs to be measured and regulated. Therefore, hybrid impedance and admittance with position control (HIPC) is required to track the trajectory and simultaneously regulate the contact torque. The literature describes two structures of HIPC: (1) a switched framework between admittance and impedance control operating in parallel (HIPCSW); and (2) a series connection between admittance and impedance control without switching. In this study, a hybrid adaptive impedance and position-based admittance control (HAIPC) in series is developed, which consists of a proportional derivative-based admittance position controller with gravitational torque compensation and an adaptive impedance controller. An extended state observer is used to estimate the interaction joint torque due to human stiff contact with the exoskeleton without the use of force/torque sensor, which is then used in the adaptive algorithm to update the stiffness and damping gains of the adaptive impedance controller. Simulation results obtained using MATLAB show that the proposed HAIPC significantly reduces the mean absolute values of the actuation torques (control inputs) required for the shoulder and elbow joints in comparison with HIPC and HIPCSW.

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Section: Interaction Force/torque Sensorless Estimationmentioning

confidence: 99%

Hybrid Adaptive Impedance and Admittance Control Based on the Sensorless Estimation of Interaction Joint Torque for Exoskeletons: A Case Study of an Upper Limb Rehabilitation Robot

Abdullahi,

Haruna,

Chaichaowarat

2024

JSAN

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“…However, the performance of the force control algorithm is still poor when the recoil force of dexterous hand is high. Kaya et al 4 proposed a force compensation method based on model to complete the estimation calculation of the environmental constrained force of multi-joint dexterous hand. The method considered a variety of constrained reaction forces at the end of the dexterous hand, but lacked the decomposition solution of the viscous friction force, making its dynamic model incomplete.…”

Section: Introductionmentioning

confidence: 99%

The adaptive neural network sliding mode control for angle/force tracking of the dexterous hand

Qin

Shi²,

Gao³

et al. 2021

Advances in Mechanical Engineering

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In order to achieve high precision control of the dexterous hand, an adaptive neural network sliding mode control algorithm based on the U-K (Udwadia-Kalaba) equation is proposed. Firstly, based on the U-K equation and considering the ideal and non-ideal constrained force at each link of the dexterous hand, the detailed dynamic equation is derived. Secondly, considering the uncertainty of the non-ideal constrained force (mainly the friction force on each link of the dexterous hand) and the chattering phenomenon when using sliding mode control alone, the adaptive neural network and the sliding mode control algorithm are combined to realize the high-precision tracking and estimation of each link angle trajectory and the non-ideal constrained force. Finally, in order to verify the correctness and rationality of the proposed algorithm, the 3-DOF spatial dexterous hand is taken as the simulated object. The simulation results show that the tracking and estimation errors of each link angle and the non-ideal constrained force are 10−2 order of magnitude.

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“…Adaptive and learning-based control methods can be considered to improve the accuracy [373], [374]. It is also important to improve the accuracy of the feedback for better results, motion models and disturbance observers can be used in this regard [375], [376].…”

Section: Actuation and Controlmentioning

confidence: 99%

Bending the rules: Magnetically-actuated surgical continuum manipulators

Thomas

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Continuum manipulators have revolutionized the field of minimally invasive surgery (MIS) in the past few decades. Major advances in fiber optics, imaging technologies, teleoperation, and haptics have accelerated the development of robot-assisted surgeries. The continuum manipulators used in robot-assisted surgery are equipped with laparoscopic tools as end effectors to augment the hand movements of the surgeon with precision. With robot assistance, surgeons can perform complex procedures inside the human body with high dexterity. However, the continuum robotics research community has challenged the lack of intuitive and effective operation of the surgical tools. Much uncertainty still exists about the tool-tissue interactions which have associated risks of tissue damage caused by unreliable control and articulation of the tool. This problem is further exacerbated by the limited visualization resolution of internal organs of the human body for safe operation. There is a pressing need to develop continuum manipulators with improved maneuverability and control to reach difficult-to-access surgical sites accurately.The aforementioned challenges of MIS play a critical role in the design and development of surgical continuum manipulators. The concept of compliant mechanisms (CMs) has been central to the design of various surgical devices. CMs are flexible mechanisms that use elastic deformation to transfer or transform force, motion, or energy. Devices made of CMs are generally monolithic in nature which leads to simplified fabrication, no wear, no friction, therefore, beneficial in high precision applications. CMs and their sub-components are increasingly used to enhance the range of motion and articulation of surgical continuum manipulators. Recently, magnetic actuation has emerged as a powerful means to execute several surgical functions such as instrument positioning, navigation, grasping, resection, and retraction. Magnetic actuation coupled with CMs has considerable impact in the design of miniaturized manipulators that eliminates the need for any cables tethered for control. Furthermore, accurate modeling of the continuum manipulators and integration of embedded sensing have been effective in the localization of manipulators. Real-time three-dimensional (3D) shape sensing of manipulators in tandem with medical imaging modalities aids in iii closed-loop control strategy to trace different trajectories with the tip of the manipulator is demonstrated. Clinical feasibility of the manipulator as a steerable catheter is shown in phantoms of a bifurcating artery and a heart with the guidance of a miniature camera.Part II explores the concept of variable stiffness mechanisms for surgical applications focusing on grasping and shape locking. Chapter 5 presents a magnetically-actuated variable stiffness robot (VSR). It is made of a soft magnetic elastomer with a sliding nitinol backbone. The synchronised retraction of the backbone with magnetic actuation leads to high deformation coiling action of the VSR. The grasping of ...

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Environmental force estimation for a robotic hand: Compliant contact detection

Cited by 4 publications

References 23 publications

Hybrid Adaptive Impedance and Admittance Control Based on the Sensorless Estimation of Interaction Joint Torque for Exoskeletons: A Case Study of an Upper Limb Rehabilitation Robot

Hybrid Adaptive Impedance and Admittance Control Based on the Sensorless Estimation of Interaction Joint Torque for Exoskeletons: A Case Study of an Upper Limb Rehabilitation Robot

The adaptive neural network sliding mode control for angle/force tracking of the dexterous hand

Bending the rules: Magnetically-actuated surgical continuum manipulators

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