The paper introduces the use of radial basis functions (RBFs) to generate smooth point-to-point joint trajectories for robot manipulators. First, Gaussian RBF interpolation is introduced taking into account boundary conditions. Then, the proposed approach is compared with classical planning techniques based on polynomial and trigonometric models. Also, the trajectory planning problem involving via-points is solved using the proposed RBF interpolation technique. The obtained trajectories are then compared with those synthesized using algebraic and trigonometric splines. Finally, the proposed method is tested for the six-joint PUMA 560 robot in two cases (minimum time and minimum time-jerk) and results are compared with those of other planning techniques. Numerical results demonstrate the advantage of the proposed technique, offering an effective solution to generate trajectories with short execution time and smooth profile.

This paper describes a simulation model for a multi-legged locomotion system with joints at the legs having viscous friction, flexibility and backlash. For that objective the robot prescribed motion is characterized in terms of several locomotion variables. Moreover, the robot body is divided into several segments in order to emulate the behaviour of an animal spine. The foot-ground interaction is modelled through a non-linear spring-dashpot system whose parameters are extracted from the studies on soil mechanics. To conclude, the performance of the developed simulation model is evaluated through a set of experiments while the robot leg joints are controlled using fractional order algorithms.

This paper investigates algorithms for enabling surgical slave robots to autonomously explore shape and stiffness of surgical fields. The paper addresses methods for estimating shape and impedance parameters of tissue and methods for autonomously exploring perceived impedance during tool interaction inside a tissue cleft. A hybrid force-motion controller and a cycloidal motion path are proposed to address shape exploration. An adaptive exploration algorithm for segmentation of surface features and a predictor-corrector algorithm for exploration of deep features are introduced based on discrete impedance estimates. These estimates are derived from localized excitation of tissue coupled with simultaneous force measurements. Shape estimation is validated in ex-vivo bovine tissue and attains surface estimation errors of less than 2.5 mm with force sensing resolutions achievable with current technologies in minimally invasive surgical robots. The effect of scan patterns on the accuracy of the shape estimate is demonstrated by comparing the shape estimate of a Cartesian raster scan with overlapping cycloid scan pattern. It is shown that the latter pattern filters the shape estimation bias due to frictional drag forces. Surface impedance exploration is validated to successfully segment compliant environments on flexible inorganic models. Simulations and experiments show that the adaptive search algorithm reduces overall time requirements relative to the complexity of the underlying structures. Finally, autonomous exploration of deep features is demonstrated in an inorganic model and ex-vivo bovine tissue. It is shown that estimates of least constraint based on singular value decomposition of locally estimated tissue stiffness can generate motion to accurately follow a tissue cleft with a predictor-corrector algorithm employing alternating steps of position and admittance control. We believe that these results demonstrate the potential of these algorithms for enabling “smart” surgical devices capable of autonomous execution of intraoperative surgical plans.

In this study, we consider a model based robust control scheme for kinematically redundant robot manipulators that also enables the use of self motion of the manipulator to perform multiple sub-tasks (e.g., maintaining manipulability, avoidance of mechanical joint limits, and obstacle avoidance). The controller proposed ensures uniformly ultimately bounded end-effector and sub-task tracking despite the parametric uncertainty associated with the dynamic model. A Lyapunov based approach has been utilized in the controller design and extension to a non minimum set of parameters for orientation representation has been presented to illustrate the flexibility of the approach. Extensive simulation studies performed initially on a 3 link planar robot arm (for the planar case) and on a six degree of freedom (DOF) Puma type robot arm (for the 3D case with quaternion feedback) are presented to demonstrate the capabilities and the performance of the controller. The results were then experimentally tested on an actual Puma 560 robot to illustrate the feasibility of the proposed method.

The design of multifunctional upper limb prosthetics has been investigated in recent years. Several areas or research need to be developed for successful implementation of dextrous upper limb prosthesis, in particular better EMG interfaces for implementing command languages.

This article introduces a novel three-bit EMG command language concept as a user interface for the multifunctional MANUS prosthesis prototype. Following the global approach proposed by MANUS, a training process and the supporting Virtual Reality training software are also presented. The last section describes the evaluation process and the results.

In this paper, we investigate trajectory tracking in a multi-input nonlinear system, where there is little knowledge of the system parameters and the form of the nonlinear function. An identification-based iterative learning control (ILC) scheme to repetitively estimate the linearity in a neighborhood of a desired trajectory is presented. Based on this estimation, the original nonlinear system can track the desired trajectory perfectly by the aid of a regional training scheme. Just like in adaptive control, a singularity exists in ILC when the input coupling matrix is estimated. Singularity avoidance is discussed. A new parameter modification procedure for ILC is presented such that the determinant of the estimate of the input coupling matrix is uniformly bounded from below. Compared with the scheme used for adaptive control of a MIMO system, the proposed scheme reduces the computation load greatly. It is used in a robotic visual system for manipulator trajectory tracking without any information about the camera-robot relationship. The estimated image Jacobian is updated repetitively and then its inverse is used to calculate the manipulator velocity without any singularity.

We present an efficient obstacle avoidance control algorithm for redundant manipulators using a new measure called collidability measure. Considering moving directions of manipulator links, the collidability measure is defined as the sum of inverse of predicted collision distances between links and obstacles: This measure is suitable for obstacle avoidance since directions of moving links are as important as distances to obstacles. For kinematic or dynamic redundancy resolution, null space control is utilized to avoid obstacles by minimizing the collidability measure: We present a velocity-bounded kinematic control law which allows reasonably large gains to improve the system performance. Also, by clarifying decomposition in the joint acceleration level, we present a simple dynamic control law with bounded joint torques which guarantees tracking of a given end-effector trajectory and improves a kinematic cost function such as collidability measure. Simulation results are presented to illustrate the effectiveness of the proposed algorithm.

A link position tracking controller is formulated for an n-link, rigid,revolute, serially-connected robot. The controller generates torque commands tothe individual robot links based on adaptive estimates of the system parametersand measurements of only link positions. A filtering technique, based on thelink position signal, is used to alleviate the need for velocity measurements. Acomplete development of the controller is presented along with a proof ofsemiglobal asymptotic link position-velocity tracking performance. Experimentalvalidation of the proposed controller on the Integrated Motion Inc. (IMI)two-link direct drive robot is also presented. Several extensions to the basiccontroller are described that consider the use of fixed parameterestimates.

A method of workspace modelling for spherical parallel manipulators (SPMs) of symmetrical architecture is developed by virtue of Euler parameters in the paper. The adoption of Euler parameters in the expression of spatial rotations of SPMs helps not only to eliminate the possible singularity in the rotation matrix, but also to formulate all equations in polynomials, which are more easily manipulated. Moreover, a homogeneous workspace can be obtained with Euler parameters for the SPMs, which facilitates the evaluation of dexterity. In this work, the problem of workspace modelling and analysis is formulated in terms of Euler parameters. An equation dealing with boundary surfaces is derived and branches of boundary surface are identified. Evaluation of dexterity is explored to quantitatively describe the capability of a manipulator to attain orientations. The singularity identification is also addressed. Examples are included to demonstrate the application of the proposed method.

Many recent developments of surgical robots focus on less invasive paradigms, such as laparoscopic SPA (Single Port Access) surgery, NOTES (Natural Orifice Translumenal Endoscopic Surgery), laryngoscopic MIS (Minimally Invasive Surgery), etc. A configuration similarity shared by these surgical robots is that two or more manipulators are inserted through one access port (a laparoscope, an endoscope, or a laryngoscope) for surgical interventions. However, upon designing such a surgical robot, the structure of the inserted manipulators has not been thoroughly explored based on evaluation of their performances. This paper presents a comparison for kinematic performances among three different continuum manipulators. They all could be applied in the aforementioned surgical robots. The structural parameters of these continuum manipulators are firstly optimized to assure a more fair and consistent comparison. This study is conducted in a dimensionless manner and provides scalable results for a wide spectrum of continuum manipulator designs as long as their segments have a constant curvature. The results could serve as a design reference for future developments of surgical robots which use one access port and continuum mechanisms.

The need to meet demanding control requirements in increasingly complex dynamical control systems under significant uncertainties makes neural networks very attractive, because of their ability to learn, to approximate functions, to classify patterns and because of their potential for massively parallel hardware implementation. This paper proposes the use of artificial neural networks (ANN) as a novel approach to the control of robot manipulators. These are part of the general class of non-linear dynamic systems where non-linear compensators are required in the controller.

This paper describes the autonomous navigation and control of an undersea vehicle using a vehicle control architecture based on the Distributed Architeclure for Mobile Navigation and a terrain-aided navigation technique based on simultaneous localisation and map building. Development of the low-speed platform models for vehicle control and the theoretical and practical details of mapping and position estimation using sonar are provided. Details of an implementation of these techniques on a small submersible vehicle “Oberon” are presented.

The paper presents structural synthesis of maximally regular T3R2-type parallel robotic manipulators (PMs) with five degrees of freedom. The moving platform has three independent translations (T3) and two rotations (R2). A method is proposed for structural synthesis of maximally regular T3R2-type PMs based on the theory of linear transformations and evolutionary morphology. A one-to-one correspondence exists between the actuated joint velocity space and the external velocity space of the moving platform. The Jacobian matrix mapping the two vector spaces of maximally regular T3R2-type PMs presented in this paper is the 5×5 identity matrix throughout the entire workspace. The condition number and the determinant of the Jacobian matrix being equal to one, the manipulator performs very well with regard to force and motion transmission capabilities. Kinematic analysis of maximally regular parallel robots is trivial and no computation is required for real-time control. This paper presents in a unified approach the structural synthesis of PMs with five degrees of freedom with decoupled and uncoupled motions, along with the maximally regular solutions.

This paper presents a solution to the global adaptive partial state feedback control problem for rigid-link, flexible-joint (RLFJ) robots. The proposed tracking controller adapts for parametric uncertainty throughout the entire mechanical system while only requiring link and actuator position measurements. A nonlinear filter is employed to eliminate the need for link velocity measurements while a set of linear filters is utilized to eliminate the need for actuator velocity measurements. A backstepping control strategy is utilized to illustrate global asymptotic link position tracking. An output feedback controller that adapts for parametric uncertainty in the link dynamics of the robot manipulator is presented as an extension. Experimental results are provided as verification of the proposed controller.

In parallel mechanisms, singular configurations (singularities) have to be avoided during motion. All the singularities should be located in order to avoid them. Hence, relationships involving all the singular platform poses (singularity locus) and the mechanism geometric parameters are useful in the design of parallel mechanisms. This paper presents a new expression of the singularity condition of the most general mechanism (6-6 FPM) of a class of parallel mechanisms usually named fully-parallel mechanisms (FPM). The presented expression uses the mixed products of vectors that are easy to be identified on the mechanism. This approach will permit some singularities to be geometrically found. A procedure, based on this new expression, is provided to transform the singularity condition into a ninth-degree polynomial equation whose unknowns are the platform pose parameters. This singularity polynomial equation is cubic in the platform position parameters and a sixth-degree one in the platform orientation parameters. Finally, how to derive the expression of the singularity condition of a specific FPM from the presented 6-6 FPM singularity condition will be shown along with an example.

The gait of a multi-segment inchworm robot is a series of actuator actions that will change the shape of the robot to generate a net motion. In this paper, we model the multi-segment inchworm robot as a finite state automaton. Gait generation is posed as a search problem on the graph described by the automaton with prescribed state transitions. The state transitions are defined based on the kinematics of robot locomotion. The auxiliary actuator concept is introduced. Single-stride and multi-stride gait generations are discussed. Single-stride gaits exhibit fault-tolerant and real-time computation features that are necessary in actual applications. Both computer simulation and experimental hardware platform are developed for various aspects of gait generation and planning.

Reliable flexible assembly workstations depend ultimately on the physics of assembly tasks performed. Multiple-peg insertions, as a practical assembly class, is complicated by the large number and kind of interaction between mating parts.

In this article, geometric and quasi-static analyses of multiple-peg insertions are presented. First, a possible contact-state enumeration, geometric conditions for each contact-state, and the force-moment equations for static-equilibrium states of two dimensional dual-peg insertions are derived. The jamming diagrams and the taxonomy of dual-peg insertions are obtained. Then, an experiment to verify the analysis is presented.

This paper presents investigations into the applications and performance of positive and negative input shapers in command shaping techniques for the vibration control of a flexible robot manipulator. A constrained planar single-link flexible manipulator is considered and the dynamic model of the system is derived using the finite element method. An unshaped bang-bang torque input is used to determine the characteristic parameters of the system for design and evaluation of the input shaping control techniques. The positive and specified amplitude negative input shapers are designed based on the properties of the system. Simulation results of the response of the manipulator to the shaped inputs are presented in the time and frequency domains. Performances of the shapers are examined in terms of level of vibration reduction, time response specifications and robustness to parameters uncertainty. The effects of derivative order of the input shaper on the performance of the system are investigated. Finally, a comparative assessment of the impact amplitude polarities of the input shapers on the system performance is presented and discussed.

Dynamic simulation of a flexible manipulator performing physical contact (including low-speed impact) tasks with stiff environment is very time consuming because very small integration step sizes have to be used for numerical stability. Existing model order reduction techniques cannot be readily applied due to the nonlinear nature of the contact dynamics. In this paper, a method is introduced to deal with this problem. The method first linearizes the contact force model on the right-hand side of the dynamics equations periodically. It then identifies the linear “stiffness” and “damping” terms from the linearized contact force model and combines them with the existing structural stiffness and damping matrices of the associated multibody system on the left-hand side of the equations. After such a process, the traditional modal analysis and reduction techniques for linear dynamic systems can be applied to reduce the order of the resulting dynamic system. Two numerical examples of flexible manipulators performing a contact task are presented to demonstrate the significant gain in computational efficiency and the improved output results.

This paper describes a new approach for estimating the vehicle motion trajectory in complex urban environments by means of visual odometry. A new strategy for robust feature extraction and data post-processing is developed and tested on-road. Images from scale-invariant feature transform (SIFT) features are used in order to cope with the complexity of urban environments. The obtained results are discussed and compared to previous works. In the prototype system, the ego-motion of the vehicle is computed using a stereo-vision system mounted next to the rear view mirror of the car. Feature points are matched between pairs of frames and linked into 3D trajectories. The distance between estimations is dynamically adapted based on re-projection and estimation errors. Vehicle motion is estimated using the non-linear, photogrametric approach based on RAndom SAmple Consensus (RANSAC). The final goal is to provide on-board driver assistance in navigation tasks, or to provide a means of autonomously navigating a vehicle. The method has been tested in real traffic conditions without using prior knowledge about the scene or the vehicle motion. An example of how to estimate a vehicle's trajectory is provided along with suggestions for possible further improvement of the proposed odometry algorithm.