RESUMEN

Tendon-sheath structures are commonly utilized to drive surgical robots due to their compact size, flexibility, and straightforward controllability. However, long-distance cable tension estimation poses a significant challenge due to its frictional characteristics affected by complicated factors. This paper proposes a miniature tension sensor array for an endoscopic cable-driven parallel robot, aiming to integrate sensors into the distal end of long and flexible surgical instruments to sense cable tension and alleviate friction between the tendon and sheath. The sensor array, mounted at the distal end of the robot, boasts the advantages of a small size (16 mm outer diameter) and reduced frictional impact. A force compensation strategy was presented and verified on a platform with a single cable and subsequently implemented on the robot. The robot demonstrated good performance in a series of palpation tests, exhibiting a 0.173 N average error in force estimation and a 0.213 N root-mean-square error. In blind tests, all ten participants were able to differentiate between silicone pads with varying hardness through force feedback provided by a haptic device.

Asunto(s)

Procedimientos Quirúrgicos Robotizados , Humanos , Procedimientos Quirúrgicos Robotizados/instrumentación , Diseño de Equipo , Robótica/instrumentación

RESUMEN

Aerial recovery and redeployment can effectively increase the operating radius and the endurance of unmanned aerial vehicles (UAVs). However, the challenge lies in the effect of the aerodynamic force on the recovery system, and the existing road-based and sea-based UAV recovery methods are no longer applicable. Inspired by the predatory behavior of net-casting spiders, this study introduces a cable-driven parallel robot (CDPR) for UAV aerial recovery, which utilizes an end-effector camera to detect the UAV's flight trajectory, and the CDPR dynamically adjusts its spatial position to intercept and recover the UAV. This paper establishes a comprehensive cable model, simultaneously considering the elasticity, mass, and aerodynamic force, and the static equilibrium equation for the CDPR is derived. The effects of the aerodynamic force and cable tension on the spatial configuration of the cable are analyzed. Numerical computations yield the CDPR's end-effector position error and cable-driven power consumption at discrete spatial points, and the results show that the position error decreases but the power consumption increases with the increase in the cable tension lower limit (CTLL). To improve the comprehensive performance of the recovery system, a multi-objective optimization method is proposed, considering the error distribution, power consumption distribution, and safety distance. The optimized CTLL and interception space position coordinates are determined through simulation, and comparative analysis with the initial condition indicates an 83% reduction in error, a 62.3% decrease in power consumption, and a 1.2 m increase in safety distance. This paper proposes a new design for a UAV aerial recovery system, and the analysis lays the groundwork for future research.

RESUMEN

The addition of geometric reconfigurability in a cable driven parallel robot (CDPR) introduces kinematic redundancies which can be exploited for manipulating structural and mechanical properties of the robot through redundancy resolution. In the event of a cable failure, a reconfigurable CDPR (rCDPR) can also realign its geometric arrangement to overcome the effects of cable failure and recover the original expected trajectory and complete the trajectory tracking task. In this paper we discuss a fault tolerant control (FTC) framework that relies on an Interactive Multiple Model (IMM) adaptive estimation filter for simultaneous fault detection and diagnosis (FDD) and task recovery. The redundancy resolution scheme for the kinematically redundant CDPR takes into account singularity avoidance, manipulability and wrench quality maximization during trajectory tracking. We further introduce a trajectory tracking methodology that enables the automatic task recovery algorithm to consistently return to the point of failure. This is particularly useful for applications where the planned trajectory is of greater importance than the goal positions, such as painting, welding or 3D printing applications. The proposed control framework is validated in simulation on a planar rCDPR with elastic cables and parameter uncertainties to introduce modeled and unmodeled dynamics in the system as it tracks a complete trajectory despite the occurrence of multiple cable failures. As cables fail one by one, the robot topology changes from an over-constrained to a fully constrained and then an under-constrained CDPR. The framework is applied with a constant-velocity kinematic feedforward controller which has the advantage of generating steady-state inputs despite dynamic oscillations during cable failures, as well as a Linear Quadratic Regulator (LQR) feedback controller to locally dampen these oscillations.

RESUMEN

Recently an active locomotive capsule endoscope (CE) for diagnosis and treatment in the digestive system has been widely studied. However, real-time localization to achieve precise feedback control and record suspicious positioning in the intestine is still challenging owing to the limitation of capsule size, relatively large diagnostic volume, and compatibility of other devices in clinical site. To address this issue, we present a novel robotic localization sensing methodology based on the kinematics of a planar cable driven parallel robot (CDPR) and measurements of the quasistatic magnetic field of a Hall effect sensor (HES) array. The arrangement of HES and the Levenberg-Marquardt (LM) algorithm are applied to estimate the position of the permanent magnet (PM) in the CE, and the planar CDPR is incorporated to follow the PM in the CE. By tracking control of the planar CDPR, the position of PM in any arbitrary position can be obtained through robot forward kinematics with respect to the global coordinates at the bedside. The experimental results show that the root mean square error (RMSE) for the estimated position value of PM was less than 1.13 mm in the X, Y, and Z directions and less than 1.14° in the θ and φ orientation, where the sensing space could be extended to ±70 mm for the given 34 × 34 mm2 HES array and the average moving distance in the Z-direction is 40 ± 2.42 mm. The proposed method of the robotic sensing with HES and CDPR may advance the sensing space expansion technology by utilizing the provided single sensor module of limited sensible volume.

Asunto(s)

Procedimientos Quirúrgicos Robotizados , Robótica , Endoscopios en Cápsulas , Diseño de Equipo , Magnetismo

RESUMEN

In a cable-driven parallel robot (CDPR), force sensors are utilized at each winch motor to measure the cable tension in order to obtain the force distribution at the robot end-effector. However, because of the effects of friction in the pulleys and the unmodeled cable properties of the robot, the measured cable tensions are often inaccurate, which causes force-control difficulties. To overcome this issue, this paper presents an artificial neural network (ANN)-based indirect end-effector force-estimation method, and its application to CDPR force control. The pulley friction and other unmodeled effects are considered as black-box uncertainties, and the tension at the end-effector is estimated by compensating for these uncertainties using an ANN that is developed using the training datasets from CDPR experiments. The estimated cable tensions at the end-effector are used to design a P-controller to track the desired force. The performance of the proposed ANN model is verified through comparisons with the forces measured directly at the end-effector. Furthermore, cable force control is implemented based on the compensated tensions to evaluate the performance of the CDPR in wrench space. The experimental results show that the proposed friction-compensation method is suitable for application in CDPRs to control the cable force.

RESUMEN

Three-dimensional (3D) printing technology has been greatly developed in the last decade and gradually applied in the construction, medical, and manufacturing industries. However, limited workspace and accuracy restrict the development of 3D printing technology. Due to the extension range and flexibility of cables, cable-driven parallel robots can be applied in challenging tasks that require motion with large reachable workspace and better flexibility. In this paper, a cable-driven parallel robot for 3D Printing is developed to obtain larger workspace rather than traditional 3D printing devices. A kinematic calibration method is proposed based on cable length residuals. On the basis of the kinematic model of the cable-driven parallel robot for 3D Printing, the mapping model is established among geometric structure errors, zero errors of the cable length, and end-effector position errors. In order to improve the efficiency of calibration measurement, an optimal scheme for measurement positions is proposed. The accuracy and efficiency of the kinematics calibration method are verified through numerical simulation. The calibration experiment based on the motion capture system indicates that the position error of end-effector is decreased to 0.6157 mm after calibration. In addition, the proposed calibration method is effective and verified for measurement positions outside optimal positions set through experiments.

RESUMEN

A cable-driven parallel robot has benefits of wide workspace, high payload, and high dynamic response owing to its light cable actuator utilization. For wide workspace applications, in particular, the body frame becomes large to cover the wide workspace that causes robot kinematic errors resulting from geometric uncertainty. However, appropriate sensors as well as inexpensive and easy calibration methods to measure the actual robot kinematic parameters are not currently available. Hence, we present a calibration sensor device and an auto-calibration methodology for the over-constrained cable-driven parallel robots using one-dimension laser distance sensors attached to the robot end-effector, to overcome the robot geometric uncertainty and to implement precise robot control. A novel calibration workflow with five phases-preparation, modeling, measuring, identification, and adjustment-is proposed. The proposed calibration algorithms cover the cable-driven parallel robot kinematics, as well as uncertainty modeling such as cable elongation and pulley kinematics. We performed extensive simulations and experiments to verify the performance of the suggested method using the MINI cable robot. The experimental results show that the kinematic parameters can be identified correctly with 0.92 mm accuracy, and the robot position control accuracy is increased by 58%. Finally, we verified that the developed calibration sensor devices and the calibration methodology are applicable to the massive-size cable-driven parallel robot system.