An extension of a model-based tracking control strategy to underactuated systems is presented. Originally, it is designed for actuated systems that can perform tasks specified by equations of algebraic or differential constraints referred to as programmed, which may be nonintegrable. It is demonstrated that for both actuated and underactuated nonholonomically constrained systems one tracking control strategy can be designed. Systems we consider are nonholonomic because of constraints put on their motions as well as unactuated degrees of freedom. We detail an example, which illustrates the theory and demonstrates advantages of application of one tracking control strategy for actuated and underactuated constrained systems.

In this paper, an adaptive control scheme is proposed for an n-link rigid robot manipulator without using the regressor. The robot is firstly modeled as a set of second-order nonlinear differential equations with the assumption that all of the matrices in that model are unavailable. Since these matrices are time-varying and their variation bounds are not given, traditional adaptive or robust designs do not apply. The function approximation technique (FAT) is used here to represent uncertainties in some finite linear combinations of orthonormal basis. The dynamics of the output tracking can thus be proved to be a stable first order filter driven by function approximation errors. Using the Lyapunov stability theory, a set of update laws is derived to give closed loop stability with proper tracking performance. Experiments are also performed on a 2-D robot to test the efficacy of the proposed scheme.

Tactile sensing is advantageous for the acquisition of local, proximal information such as the contact condition between a finger and an object. This type of sensing, however, is not suited for recognizing an entire object that is easily recognized by vision. The objective of this paper is to ease the limitations experienced in tactile sensing by using both a neural model based on the human tactile sensation and a tactile-oriented associative memory model to enable a robot to recognize object contours. In the model, first the direction vectors belonging to segments of the object contour are obtained from a filtered tactile pattern of the simulated neurons' excitation. Second, the vectors are quantized by the chain-symbolizing method and stored for use in a memory matrix that accumulates matrix-products between the vector and its transposition. In the recalling process, complete vectors are remembered even if some input vector elements are missing. In the experiments, a robotic manipulator equipped with a tactile sensor traces five types of contours, these being a circle, a square, a triangle, a star, and a hexagon. After the robot recalls the complete contours, it is able to recognize a complete contour by just touching even a part of a contour.

This paper deals with the design and the experiments of the upper part of the ROBIAN biped robot. The motivation of the ROBIAN project is related to the study of the human being locomotion system. The major application of ROBIAN prototype is the development of a real testing bed of active/passive prosthesis devices enhancing research on the human being locomotion mechanism handicaps. The analysis of the wrench six components exerted by the upper part of a virtual manikin on the locomotion apparatus leads to the identification of two coupling relations. Based on the dynamic equivalence concept between mechanisms, the ROBIAN torso mechanism is identified. This concept leads to a four degrees of freedom mechanism able to reproduce the dynamic effects of the upper limbs during the walking gait. The mechanism parameters are optimized with respect to several design criteria and constraints. Then the prototype is built and mounted on the ROBIAN locomotion apparatus through a six components force sensor. Experimental results presented in this paper validate the proposed approach. The experimental coupling coefficients are identified. The influence of the masses motion on the ZMP trajectory are also given, showing the effectiveness of the torso mechanism contribution during a walking gait.

Once the path of the vehicle and the desired task of the end-effector are predefined, in order to apply the optimal stability criterion, the manipulator should be redundant. In this paper, the goal is to find the position, angular velocity, and angular acceleration of the redundant link of the manipulator such that the entire system becomes optimally stable. By considering the full dynamic interaction between the manipulator and its vehicle, the stability issue becomes more complex. There are some measures of stability and one of them is the tire's upward force. This measure tries to equalize the upward forces of the tires that lead to optimal stability and better steer-ability. Optimizing the parameters of various engineering problems is a challenging issue. In this research, the optimal position, angular velocity, and angular acceleration of the redundant link are found by the genetic algorithm approach such that the upward forces of vehicle tires are nearly equal. Furthermore, the effectiveness of this procedure is shown by presenting an example.

In the paper we address a problem of controlling an oscilmotion with a robot. As the object we have selected a yo-yo. First we have measured and analysed the motion of different yo-yos. We have developed a simplified model of a yo-yo which has one degree-of-freedom, and the behaviour at the end of the string is modelled as an impact. Next, we discuss the control strategy. Our results show, that for playing a yo-yo it is important to start the upward motion before the yo-yo reaches the bottom position and the acceleration has to be reversed after the bottom impact. We present two control strategies: one based on predefined hand motion pattern and and the other generating the hand motion on-line. Both allow playing the yo-yo at a selected top height. The theoretical results have been proven by experiments on a real robot system.

The paper presents a control oriented dynamic formulation for constrained robotic systems. We refer to this formulation as control oriented since it can be directly applied to design a model-based tracking control strategy. It enables one to obtain dynamic models for systems subjected to material constraints and non-material referred to as program constraints. The dynamic model for a constrained robot, where equations of program constraints specify tasks and motion requirements, is used as a program motion planner for a controller design. The formulation provides a theoretical framework, which is a basis for the study of robot performance of constrained tasks. Examples of developments of control oriented dynamic models are presented, and their applications for control are demonstrated and discussed.

Significant research has been aimed at the development and control of teleoperator systems due to both the practical importance and the challenging theoretical nature of the problem. Two controllers are developed in this paper for a nonlinear teleoperator system that target coordination of the master and slave manipulators and passivity of the overall system. The first controller is proven to yield a semi-global asymptotic result in the presence of parametric uncertainty in the master and slave manipulator dynamic models. The second controller yields a global asymptotic result despite unmeasurable user and environmental input forces. To develop each controller, a transformation encodes the coordination and passivity objectives in the closed loop system. The coordinated system is forced to track a dynamic system to assist in meeting all control objectives. Finally, continuous nonlinear integral feedback terms are used to accommodate for incomplete system knowledge for both controllers. Lyapunov-based techniques are used to prove that all control objectives are met and that all signals are bounded.

In this work, a hybrid adaptive/learning controller is simulated in Simulink using a two-link robot manipulator for a sinusoidal desired position. The two-dimensional nature of control law makes direct simulation difficult. Simulation results demonstrate that the controller achieves semi global asymptotic position tracking.

In this article, impedance control of a two link flexible link manipulators is addressed. The concept of impedance control of flexible link robots is rather new and is being addressed for the first time by the authors. Impedance Control provides a universal approach to the control of flexible robots, in both constrained and unconstrained maneuvers. The initial part of the paper concerns the use of Hamilton's principle to derive the mathematical equations governing the dynamics of joint angles, vibration of the flexible links and the constraining forces. The approximate elastic deformations are then derived by means of the Assumed-Mode-Method (AMM). Using the singular perturbation method, the dynamic of the manipulator is decomposed into fast and slow subsystems. The slow dynamic corresponds to the rigid manipulator and the fast dynamic is due to vibrations of flexible links. The sliding mode control (SMC) theory has been used as the means to achieve the 2nd order target impedance for the slow dynamics. A controller based on state feedback is also designed to stabilize the fast dynamics. The composite controller is constructed by using the slow and fast controllers. Simulation results for a 2-DOF robot in which only the 2nd link is flexible confirm that the controller performs remarkably well under various simulation conditions.

This paper addresses the design of a 2-dof novel flexible parallel robot that maximizes the fundamental frequency of vibration under a specified total weight constraint. In order to enhance the natural frequency of the robot in the direction Z, structure modification of the robot is made based on the initial project. The proposed robot is suitable for the application that requires high-speed motion in a plane and step-by-step, or relatively low speed on the orthogonal direction.

We combine a “hybrid” force-/position-control scheme with a potential field approach into a novel method for collision recovery and navigation in unknown environments. It can be implemented both on manipulators and mobile robots. The use of force sensors allows us to locally sense the environment and design a dynamic control law. Multiple Lyapunov functions are used to establish asymptotic stability of the closed-loop system. The switching conditions and stability criteria are established under reasonable assumptions on the type of obstacles present in the environment. Extensive simulation results are presented to illustrate the system behavior under the designed control scheme, and verify its stability, collision recovery, and navigation properties.

This paper focuses on the structure and property of the singularity loci of the 3/6-Stewart-Gough platform for general orientations. Based on the singularity kinematics principle, a planar singularity-equivalent-mechanism is proposed, by which the complicated singularity analysis of that parallel mechanism is transformed into a simpler position analysis of the planar mechanism. All the possible positions of the planar mechanism form the singularity loci of the 3/6-Stewart-Gough manipulator. The result shows that the singularity equation become quite simple moreover the structure and property of the singularity loci are also identified and explained. For the most general orientations of the typical 3/6-Stewart-Gough platform, the singularity locus equation is a special irresolvable polynomial expression of degree three, which in infinite parallel principal sections includes a parabola, four pairs of intersecting straight lines and infinity of hyperbolas. This result is beneficial to analysis of the similar issue of other Stewart-Gough manipulators.

A stochastic ellipsoid modelling of repeatability is proposed for industrial manipulator robots. The covariance matrix of angular position is determined introducing the jump process, which reveals to be a first and second order stationary Gaussian process.

From this accurate covariance matrix, the stochastic ellipsoid theory gives the density of position in the workspace around the mean position. Hence the pose repeatability index can be computed in different locations. Computed and experimental repeatability are compared. Experimental repeatability variability is studied. A new “intrinsic repeatability index” is proposed. In conclusion, the modelling reflects well the location and load influence on the repeatability.

Increasing the energy autonomy of a hopping one-legged robot is studied in this paper. For a particular passive gait, of all those possible, the energy dissipated per unit length of travel is shown to be less than for any other gait. This optimal gait is identified analytically, by exploiting the commonly used SLIP model to simplify real robot dynamics. Both mechanical and electrical losses are considered. The accuracy of the optimal gait analytical prediction is evaluated by a numerical analysis of a realistic robot model. Finally, restrictions imposed on executing the optimal gait due to motor limitations are studied.

In this paper, the joint angles of a two link planar manipulator are calculated by using inverse kinematics equations together with some geometric equalities. For a given position of the end-effector the joint angle and angular velocity of the links are derived. The analyses contains many equations which have to be solved. However, the solutions are rather cumbersome and complicated, therefore a program is written in Fortran 90 in order to do, the whole calculation and data collection. The results are given at the end of this paper.

This paper discusses the modeling and control of a robotic manipulator with a new deburring tool, which integrates two pneumatic actuators to take advantage of a double cutting action. A coordination control method is developed by decomposing the robotic deburring system into two subsystems; the arm and the deburring tool. A decentralized control approach is pursued, in which suitable controllers were designed for the two subsystems in the coordination scheme. In simulation, three different tool configurations are considered: rigid, single pneumatic and integrated pneumatic tools. A comparative study is performed to investigate the deburring performance of the deburring arm with the different tools. Simulation results show that the developed robotic deburring system significantly improves the accuracy of the deburring operation.

Non-overconstrained 3-dof spherical parallel manipulators of a structural type 3-RCC, 3-CCR, 3-CRC are introduced. The mechanism has three limbs that connect in parallel the moving platform to the fixed base. Each limb is an opened kinematic chain made of a sequence of one revolute pair R and two cylindrical pairs C. The orientation of the end-effector is obtained by actuating simultaneously the three limbs. A structural type analysis and synthesis, which is based on the algebraic properties of a Lie group of the displacement set, is employed to find the geometrical conditions for the assembly of these spherical parallel mechanisms and also the structurally singular configurations. Then an enumeration of the structural types is given and remarkable special cases of orientational mechanisms are also described, namely 3-HGR, 3-RGH and 3-HGH.

The workspace boundary of 6-DOF parallel manipulators is a two-dimensional surface consisting of many patches that can be obtained by solving different sets of four constraint equations. This paper proposes algorithms for finding the equations to generate each patch of the boundary. Methods involving a searching technique are first developed to generate some small subsets of the boundary. The obtained data are then used to predict the equations for generating the rest of the boundary.

A new promising approach for visibility-sensitive path-planning problems is presented. The paper focuses on covert navigation where a mobile robot needs to plan a stealthy path to approach a designated destination in a cluttered environment. The aim is to minimize the robot's exposure to hostile sentries within the same environment. The approach can be adapted to work with different levels of initial knowledge the robot may have about both the environment map and the sentries' locations. The approach depends on estimating a cost value at each free-space location that presents the risk of being seen by any sentry. Based on the distance transform algorithm methodology, the minimum visibility–distance cost to a goal is calculated at each cell in the grid-based environment map. Moving along the steepest descent trajectory from any starting point generates an optimal covert path to a goal. The approach has been evaluated with both simulated and physical experiments. A number of test cases are presented. In each case, a path with considerable covertness, compared to a short path to the same destination, is generated. In addition to covert navigation, the approach is introduced briefly as a potential solution for other visibility-based path-planning problems.