Sensor technology for advanced space missions

The capability and applications of two sensors, Spatial, High-Accuracy, Position-Encoding Sensor (SHAPES) and Fiber Optics Rotation Sensor (FORS), for advanced missions are discussed. The multiple target, 3-D position sensing capability of SHAPES meets a critical technology need for many developing applications. A major milestone of the SHAPES task was completed on schedule on May 30, 1986, by demonstrating simultaneous ranging to eight moving targets at a rate of 10 measurements per second. The range resolution to static target was shown to be 25 microns. SHAPES scheduled technology readiness will support the sensor needs of a number of early users. The next phase in the development of SHAPES is to incorporate an angular measurement CCD to provide the full 3-dimensional sensing. A flight unit design and fabrication can be complete by FY89. FORS, with its significant improvement over present technology in lifetime, performance, weight, power, and recurrent cost, will be an important technology for future space systems. Technology readiness will be demonstrated with a FORS brassboard with fully integrated IO chips by FY88. The unique capability of miniature remote sensing heads, connected to a central system, will open up new areas in control and stability of large space structures. This application requires additional study

Shape sensing of miniature snake-like robots using optical fibers

Snake like continuum robots are increasingly used for minimally invasive surgery. Most robotic devices of this sort that have been reported to date are controlled in an open loop manner. Using shape sensing to provide closed loop feedback would allow for more accurate control of the robot's position and, hence, more precise surgery. Fiber Bragg Gratings, magnetic sensors and optical reflectance sensors have all been reported for this purpose but are often limited by their cost, size, stiffness or complexity of fabrication. To address this issue, we designed, manufactured and tested a prototype two-link robot with a built-in fiber-optic shape sensor that can deliver and control the position of a CO 2 -laser fiber for soft tissue ablation. The shape sensing is based on optical reflectance, and the device (which has a 4 mm outer diameter) is fabricated using 3D printing. Here we present proof-of-concept results demonstrating successful shape sensing - i.e. measurement of the angular displacement of the upper link of the robot relative to the lower link - in real time with a mean measurement error of only 0.7°

Local sensory control of a dexterous end effector

A numerical scheme was developed to solve the inverse kinematics for a user-defined manipulator. The scheme was based on a nonlinear least-squares technique which determines the joint variables by minimizing the difference between the target end effector pose and the actual end effector pose. The scheme was adapted to a dexterous hand in which the joints are either prismatic or revolute and the fingers are considered open kinematic chains. Feasible solutions were obtained using a three-fingered dexterous hand. An algorithm to estimate the position and orientation of a pre-grasped object was also developed. The algorithm was based on triangulation using an ideal sensor and a spherical object model. By choosing the object to be a sphere, only the position of the object frame was important. Based on these simplifications, a minimum of three sensors are needed to find the position of a sphere. A two dimensional example to determine the position of a circle coordinate frame using a two-fingered dexterous hand was presented

Development of a fiber-based shape sensor for navigating flexible medical tools

Robot-assisted minimally invasive surgical procedure (RAMIS) is a subfield of minimally invasive surgeries with enhanced manual dexterity, manipulability, and intraoperative image guidance. In typical robotic surgeries, it is common to use rigid instruments with functional articulating tips. However, in some operations where no adequate and direct access to target anatomies is available, continuum robots can be more practical, as they provide curvilinear and flexible access. However, their inherent deformable design makes it difficult to accurately estimate their 3D shape during the operation in real-time. Despite extensive model-based research that relies on kinematics and mechanics, accurate shape sensing of continuum robots remains challenging. The state-of-the-art tracking technologies, including optical trackers, EM tracking systems, and intraoperative imaging modalities, are also unsuitable for this task, as they all have shortcomings. Optical fiber shape sensing solutions offer various advantages compared to other tracking modalities and can provide high-resolution shape measurements in real-time. However, commercially available fiber shape sensors are expensive and have limited accuracy. In this thesis, we propose two cost-effective fiber shape sensing solutions based on multiple single-mode fibers with FBG (fiber Bragg grating) arrays and eccentric FBGs. First, we present the fabrication and calibration process of two shape sensing prototypes based on multiple single-mode fibers with semi-rigid and super-elastic substrates. Then, we investigate the sensing mechanism of edge-FBGs, which are eccentric Bragg gratings inscribed off-axis in the fiber's core. Finally, we present a deep learning algorithm to model edge-FBG sensors that can directly predict the sensor's shape from its signal and does not require any calibration or shape reconstruction steps. In general, depending on the target application, each of the presented fiber shape sensing solutions can be used as a suitable tracking device. The developed fiber sensor with the semi-rigid substrate has a working channel in the middle and can accurately measure small deflections with an average tip error of 2.7 mm. The super-elastic sensor is suitable for measuring medium to large deflections, where a centimeter range tip error is still acceptable. The tip error in such super-elastic sensors is higher compared to semi-rigid sensors (9.9-16.2 mm in medium and large deflections, respectively), as there is a trade-off between accuracy and flexibility in substrate-based fiber sensors. Edge-FBG sensor, as the best performing sensing mechanism among the investigated fiber shape sensors, can achieve a tip accuracy of around 2 mm in complex shapes, where the fiber is heavily deflected. The developed edge-FBG shape sensing solution can compete with the state-of-the-art distributed fiber shape sensors that cost 30 times more

Computed torque control of a free-flying cooperat ing-arm robot

The unified approach to solving free-floating space robot manipulator end-point control problems is presented using a control formulation based on an extension of computed torque. Once the desired end-point accelerations have been specified, the kinematic equations are used with momentum conservation equations to solve for the joint accelerations in any of the robot's possible configurations: fixed base or free-flying with open/closed chain grasp. The joint accelerations can then be used to calculate the arm control torques and internal forces using a recursive order N algorithm. Initial experimental verification of these techniques has been performed using a laboratory model of a two-armed space robot. This fully autonomous spacecraft system experiences the drag-free, zero G characteristics of space in two dimensions through the use of an air cushion support system. Results of these initial experiments are included which validate the correctness of the proposed methodology. The further problem of control in the large where not only the manipulator tip positions but the entire system consisting of base and arms must be controlled is also presented. The availability of a physical testbed has brought a keener insight into the subtleties of the problem at hand

Teleoperation of MRI-Compatible Robots with Hybrid Actuation and Haptic Feedback

Image guided surgery (IGS), which has been developing fast recently, benefits significantly from the superior accuracy of robots and magnetic resonance imaging (MRI) which is a great soft tissue imaging modality. Teleoperation is especially desired in the MRI because of the highly constrained space inside the closed-bore MRI and the lack of haptic feedback with the fully autonomous robotic systems. It also very well maintains the human in the loop that significantly enhances safety. This dissertation describes the development of teleoperation approaches and implementation on an example system for MRI with details of different key components. The dissertation firstly describes the general teleoperation architecture with modular software and hardware components. The MRI-compatible robot controller, driving technology as well as the robot navigation and control software are introduced. As a crucial step to determine the robot location inside the MRI, two methods of registration and tracking are discussed. The first method utilizes the existing Z shaped fiducial frame design but with a newly developed multi-image registration method which has higher accuracy with a smaller fiducial frame. The second method is a new fiducial design with a cylindrical shaped frame which is especially suitable for registration and tracking for needles. Alongside, a single-image based algorithm is developed to not only reach higher accuracy but also run faster. In addition, performance enhanced fiducial frame is also studied by integrating self-resonant coils. A surgical master-slave teleoperation system for the application of percutaneous interventional procedures under continuous MRI guidance is presented. The slave robot is a piezoelectric-actuated needle insertion robot with fiber optic force sensor integrated. The master robot is a pneumatic-driven haptic device which not only controls the position of the slave robot, but also renders the force associated with needle placement interventions to the surgeon. Both of master and slave robots mechanical design, kinematics, force sensing and feedback technologies are discussed. Force and position tracking results of the master-slave robot are demonstrated to validate the tracking performance of the integrated system. MRI compatibility is evaluated extensively. Teleoperated needle steering is also demonstrated under live MR imaging. A control system of a clinical grade MRI-compatible parallel 4-DOF surgical manipulator for minimally invasive in-bore prostate percutaneous interventions through the patient’s perineum is discussed in the end. The proposed manipulator takes advantage of four sliders actuated by piezoelectric motors and incremental rotary encoders, which are compatible with the MRI environment. Two generations of optical limit switches are designed to provide better safety features for real clinical use. The performance of both generations of the limit switch is tested. MRI guided accuracy and MRI-compatibility of whole robotic system is also evaluated. Two clinical prostate biopsy cases have been conducted with this assistive robot

Design and Evaluation of a 3-D Printed Optical Sensor for Monitoring Finger Flexion

The development of techniques for monitoring finger movement is becoming increasingly important in areas, such as robotics, virtual reality, and rehabilitation. To date, various techniques have been proposed for tracking hand movements, but the majority suffer from poor accuracy and repeatability. Inspired by the articulated structure of finger joints, we propose a novel 3-D printed optical sensor with a compact hinged configuration for tracking finger flexion. This sensor exploits Malus' law using the attenuation of light transmitted through crossed polarizers. The sensor consists of a single LED, two pieces of linear polarizing film, and a photodetector that detects the changes in polarized light intensity proportional to the angle of finger flexion. This paper presents the characterization of the proposed optical sensor and compares it with a commonly used commercial bend sensor. Results show that the bend sensor exhibits hysteresis error, low sensitivity at small angles, and significant temporal drift. In contrast, the optical sensor is more accurate (±0.5°) in the measuring range from 0° to 90°, and exhibits high repeatability and stability, as well as a fast dynamic response. Overall, the optical sensor outperforms the commercial bend sensor, and shows excellent potential for monitoring hand movements in real time