Rajnikant V. Patel

A stable neural network-based observer with application to flexible-joint manipulators

A stable neural network (NN)-based observer for general multivariable nonlinear systems is presented in this paper. Unlike most previous neural network observers, the proposed observer uses a nonlinear-in-parameters neural network (NLPNN). Therefore, it can be applied to systems with higher degrees of nonlinearity without any a priori knowledge about system dynamics. The learning rule for the neural network is a novel approach based on the modified backpropagation (BP) algorithm. An e-modification term is added to guarantee robustness of the observer. No strictly positive real (SPR) or any other strong assumption is imposed on the proposed approach. The stability of the recurrent neural network observer is shown by Lyapunovs direct method. Simulation results for a flexible-joint manipulator are presented to demonstrate the enhanced performance achieved by utilizing the proposed neural network observer.

High-Fidelity Bilateral Teleoperation Systems and the Effect of Multimodal Haptics

In master-slave teleoperation applications that deal with a delicate and sensitive environment, it is important to provide haptic feedback of slave/environment interactions to the users hand as it improves task performance and teleoperation transparency (fidelity), which is the extent of telepresence of the remote environment available to the user through the master-slave system. For haptic teleoperation, in addition to a haptics-capable master interface, often one or more force sensors are also used, which warrant new bilateral control architectures while increasing the cost and the complexity of the teleoperation system. In this paper, we investigate the added benefits of using force sensors that measure hand/master and slave/environment interactions and of utilizing local feedback loops on the teleoperation transparency. We compare the two-channel and the four-channel bilateral control systems in terms of stability and transparency, and study the stability and performance robustness of the four-channel method against nonidealities that arise during bilateral control implementation, which include master-slave communication latency and changes in the environment dynamics. The next issue addressed in the paper deals with the case where the master interface is not haptics capable, but the slave is equipped with a force sensor. In the context of robotics-assisted soft-tissue surgical applications, we explore through human factors experiments whether slave/environment force measurements can be of any help with regard to improving task performance. The last problem we study is whether slave/environment force information, with and without haptic capability in the master interface, can help improve outcomes under degraded visual conditions.

A layered goal-oriented fuzzy motion planning strategy for mobile robot navigation

Most conventional motion planning algorithms that are based on the model of the environment cannot perform well when dealing with the navigation problem for real-world mobile robots where the environment is unknown and can change dynamically. In this paper, a layered goal-oriented motion planning strategy using fuzzy logic is developed for a mobile robot navigating in an unknown environment. The information about the global goal and the long-range sensory data are used by the first layer of the planner to produce an intermediate goal, referred to as the way-point, that gives a favorable direction in terms of seeking the goal within the detected area. The second layer of the planner takes this way-point as a subgoal and, using short-range sensory data, guides the robot to reach the subgoal while avoiding collisions. The resulting path, connecting an initial point to a goal position, is similar to the path produced by the visibility graph motion planning method, but in this approach there is no assumption about the environment. Due to its simplicity and capability for real-time implementation, fuzzy logic has been used for the proposed motion planning strategy. The resulting navigation system is implemented on a real mobile robot, Koala, and tested in various environments. Experimental results are presented which demonstrate the effectiveness of the proposed fuzzy navigation system.

Modeling and Control of Shape Memory Alloy Actuators

This brief describes a new model for shape memory alloy (SMA) actuators based on the physics of the process and develops control strategies using the model. The model consists of three equations - the temperature dynamics described by Joules heating-convectional cooling, the mole fraction distribution with temperature given by statistics to describe a two state system, and a constitutive equation relating the changes in temperature and mole fraction to the stress and strain induced in the SMA. This model is used to develop two control schemes for controlling the strain in an SMA actuator. The first control scheme describes a gain-scheduled proportional-integral (PI) controller, the gains of which are obtained by means of linear quadratic regulator (LQR) optimization. The second control scheme is an Hinfin loop-shaping controller using normalized coprime stabilization which ensures robust stability by minimizing the effect of unmodeled dynamics at high frequencies. Simulation and experimental results show fast and accurate control of the strain in the SMA actuator for both control schemes.

An integral manifold approach for tip-position tracking of flexible multi-link manipulators

In this paper, a nonlinear control strategy for tip position trajectory tracking of a class of structurally flexible multilink manipulators is developed. Using the concept of integral manifolds and singular perturbation theory, the full-order flexible system is decomposed into corrected slow and fast subsystems. The tip-position vector is similarly partitioned into corrected slow and fast outputs. To ensure an asymptotic tracking capability, the corrected slow subsystem is augmented by a dynamical controller in such a way that the resulting closed-loop zero dynamics are linear and asymptotically stable. The tracking problem is then redefined as tracking the slow output and stabilizing the corrected fast subsystem by using dynamic output feedback. Consequently, it is possible to show that the tip position tracking errors converge to a residual set of O(/spl epsiv//sup 2/), where /spl epsiv/ is the singular perturbation parameter. A major advantage of the proposed strategy is that the only measurements required are the tip positions, joint positions, and joint velocities. Experimental results for a single-link arm are also presented and compared with the case when the slow control is designed based on the rigid-body model of the manipulator.

Modified Newton's method applied to potential field-based navigation for mobile robots

This paper investigates the inherent oscillation problem of potential field methods (PFMs) in the presence of obstacles and in narrow passages. These problems can cause slow progress and system instability in implementation. To overcome these two problems, in this paper, we propose a modification of Newtons method. The use of the modified Newtons method, which applies anywhere C/sub 2/ continuous navigation functions are defined, greatly improves system performance when compared to the standard gradient descent approach. To the best of our knowledge, ours is the first systematic approach to the oscillation problems in PFMs. We have validated this technique by comparing its performance with the gradient descent method in obstacle-avoidance tasks with different potential models and parameter changes.

Robot-assisted Tactile Sensing for Minimally Invasive Tumor Localization

The 10 mm incisions used in minimally invasive cancer surgery prevent the direct palpation of internal organs, making intraoperative tumor localization difficult. A tactile sensing instrument (TSI), which uses a commercially available sensor to measure distributed pressure profiles along the contacting surface, has been developed to facilitate remote tissue palpation. The objective of this research is to assess the feasibility of using the TSI under robotic control to reliably locate underlying tumors while reducing collateral tissue trauma. The performance of humans and a robot using the TSI to locate tumor phantoms embedded into ex vivo bovine livers is compared. An augmented hybrid impedance control scheme has been implemented on a Mitsubishi PA10-7C to perform the force/position control used in the trials. The results show that using the TSI under robotic control realizes an average 35% decrease in the maximum forces applied and a 50% increase in tumor detection accuracy when compared to manual manipulation of the same instrument. This demonstrates that the detection of tumors using tactile sensing is highly dependent on how consistently the forces on the tactile sensing area are applied, and that robotic assistance can be of great benefit when trying to localize tumors in minimally invasive surgery.

Brief Nonlinear tip-position tracking control of a flexible-link manipulator: theory and experiments

This paper presents an observer-based inverse dynamics control strategy that results in small tip-position tracking errors while maintaining robust closed-loop performance for a class of multi-link structurally flexible manipulators. This is done by defining new outputs near the end points of the arms as well as by augmenting the control inputs by terms which ensure stable operation of the closed-loop system. As part of the control design, a nonlinear observer is introduced to estimate the rates of change of flexible modes. Experimental results are given for the case of a two-link manipulator with a flexible link that further confirm the theoretical and simulation results.

Friction Identification and Compensation in Robotic Manipulators

In this paper, friction identification and friction compensation in the joints of a robotic manipulator are studied. The friction force is modeled using a single-state dynamic model that is utilized in the friction compensation algorithm. A new method for identifying the parameters of the aforementioned model in a robotic manipulator is presented. To evaluate the performance of this method, two different manipulators with different friction characteristics are examined. A 2-DOF manipulator that is used for high-speed micrometer precision manipulation and a 4-DOF macromanipulator that is used for long-reach positioning tasks are considered. It is shown that despite the different nature of the two manipulators, the same method can effectively improve the speed, accuracy, and smoothness of the manipulation in both cases.

Autonomous Image-Guided Robot-Assisted Active Catheter Insertion

Interventional cardiologists are at great risk from radiation exposure due to lengthy procedures performed under X-ray radiations. Angioplasty is one such procedure wherein the clinician guides a catheter into the femoral artery under X-rays and the procedure often extends to over 50 min. A clinician performs several hundred such procedures over his/her lifetime, leading to an accumulation of the total radiation he/she is exposed to. In this paper, we investigate autonomous robot-assisted insertion of an active catheter instrumented with shape memory alloy (SMA) actuators using image guidance. The tip of the active catheter is tracked in real time to provide information on the location of the catheter that determines the optimal stroke length of insertion for the robot and the necessary bending angle for the active catheter. The catheter is autonomously guided from the point of entry to the site of plaque buildup, thereby shielding the clinician from harmful radiation due to the X-rays used for imaging and providing a more ergonomic approach for catheter insertion. Experimental results are given to illustrate the robot-assisted catheter insertion procedure using image guidance.