An approach for calculating the maximum possible absolute values of joint velocities or generalized reactions in a leg of a parallel mechanism has been considered in this paper. The Jacobian analysis and the Screw theory-based methods have been used to acquire the result. These values are calculated for the “worst” directions of the external load or end-effector’s velocity for each leg. The feasibility of using these parameters as the measures of closeness to different types of parallel mechanism singularity is discussed. Further, how this approach is related to the state-of-the-art methods has been illustrated. The key aspect of the discussed approach is that the normalization of vectors or screws is carried out separately for angular and linear components. One possible advantage of such an approach is that it deals only with the kinematic and statics of the mechanism while still providing physically meaningful and practically applicable measures. Case studies of a 3-Degrees Of Freedom translational parallel mechanism and a planar parallel mechanism are presented for illustration and comparison.

Efficient algorithm integration is a key issue in aerial robotics. However, only a few integration solutions rely on a cognitive approach. Cognitive approaches break down complex problems into independent units that may deal with progressively lower-level data interfaces, all the way down to sensors and actuators. A cognitive architecture defines information flow among units to produce emergent intelligent behavior. Despite the improvements in autonomous decision-making, several key issues remain open. One of these issues is the selection, coordination, and decision-making related to the several specialized tasks required for fulfilling mission objectives. This work addresses decision-making for the cognitive unmanned-aerial-vehicle architecture coined as ARCog. The proposed architecture lays the groundwork for the development of a software platform aligned with the requirements of the state-of-the-art technology in the field. The system is designed to provide high-level decision-making. Experiments prove that ARCog works correctly in its target scenario.

This paper presents a vision-based path planning strategy that aims to reduce the computational time required by a robot to find a feasible path from a starting point to the goal point. The proposed algorithm presents a novel strategy that can be implemented on any well-known path planning algorithm such as A*, D* and probabilistic roadmap (PRM), to improve the swiftness of these algorithms. This path planning algorithm is suitable for real-time scenarios since it reduces the computational time compared to the basis and traditional algorithms. To test the proposed path planning strategy, a tracking control strategy is implemented on a mobile platform. This control strategy consists of three major stages. The first stage deals with gathering information about the surrounding environment using vision techniques. In the second stage, a free-obstacle path is generated using the proposed reduced scheme. In the final stage, a Lyapunov kinematic tracking controller and two Artificial Neural Network (ANN) based-controllers are implemented to track the proposed path by adjusting the rotational and linear velocity of the robot. The proposed path planning strategy is tested on a Pioneer P3-DX differential wheeled mobile robot and an Xtion PRO depth camera. Experimental results prove the efficiency of the proposed path planning scheme, which was able to reduce the computational time by a large percentage which reached up to 88% of the time needed by the basis and traditional scheme, without significant adverse effect on the workability of the basis algorithm. Moreover, the proposed path planning algorithm has improved the path efficiency, in terms of the path length and trackability, challenging the traditional trade-off between swiftness and path efficiency.

Most of the previous works on the motion control of autonomous underwater vehicles (AUVs) assume that (i) the vehicle actuators are able to tolerate every level of the control signals, and (ii) the vehicle is equipped with the velocity sensors in all degrees of freedom. These assumptions are not desirable in practice. Toward this end, this paper addresses the trajectory tracking control of the underactuated AUVs with the limited torque, without the velocity measurements and under environmental disturbances in a three-dimensional space. At first, a variable transformation is introduced which helps us to derive a second-order dynamic model for underactuated AUVs. Then, a saturated tracking controller is proposed by employing the saturation functions to bound the closed-loop error variables. This technique reduces the risk of the actuators saturation by decreasing the amplitude of the generated control signals. In addition, a nonlinear saturated observer is introduced to remove the velocity sensors from the control system. The proposed controller copes with the uncertain vehicle parameters, and constant or time-varying environmental disturbances induced by the waves and ocean currents. Lyapunov's direct method is used to show the semi-global uniform ultimate boundedness of the tracking and state estimation errors. Finally, some simulation results illustrate the effectiveness of the proposed controller.

Many robotic tasks require the end-effector to come into contact with the external environment. In such complex tasks, the manipulator is constrained by the environment, and certain DOFs are lost for motion. The contact forces must be controlled in constraint directions, while the tip position is simultaneously controlled in the free directions.

An iterative learning control method is proposed for a class of non-linear dynamic systems with uncertain parameters. The method, in which non-linear system model is used, employs the model algorithmic control concept in the iteration sequence. A sufficient condition for convergency is provided. Then the method is shown to be applicable to continuous-path control of a robot manipulator.

In medical interventional procedures such as brachytherapy, biopsy and radio-frequency ablation, precise tracking through the preplanned desired trajectory is very essential. This important requirement is critical due to two major reasons: anatomical obstacle avoidance and accurate targeting for avoiding undesired radioactive dose exposure or damage to neighboring tissue and critical organs. Therefore, a precise control of the needling device in the unstructured environment in the presence of external disturbance is required to achieve accurate target reaching in clinical applications. In this paper, a shape memory alloy actuated active flexible needle controlled by an adaptive sliding mode controller is presented. The trajectory tracking performance of the needle is tested while having its actual movement in an artificial tissue phantom by giving various input reference trajectories such as multi-step and sinusoidal. Performance of the adaptive sliding mode controller is compared with that of the proportional, integral and derivative controller and is proved to be the effective method in the presence of the external disturbances.

The weightless planar 2R underactuated manipulators with passive last joint are considered in this paper for investigating a feasible method to stabilize the system, which is a second-order nonholonomic-constraint mechanical system with drifts. The characteristics including the controllability of the linear approximation model, the minimum phase property, the Small Time Local Controllability (STLC), the differential flatness, and the exactly nilpotentizable properties, are analyzed. Unfortunately, these negative characteristics indicate that the simplest underactuated mechanical system is difficult to design a stable closed-loop control system. In this paper, nilpotent approximation and iterative steering methods are utilized to solve the problem. A globally effective nilpotent approximation model is developed and the parameterized polynomial input is adopted to stabilize the system to its non-singularity equilibrium configuration. In accordance with this scheme, it is shown that designing a stable closed-loop control system for the underactuated mechanical system can be ascribed to solving a set of nonlinear algebraic equations. If the nonlinear algebraic equations are solvable, then the controller is asymptotically stable. Some numerical simulations demonstrate the effectiveness of the presented approach.

A planar underactuated bipedal robot with an impulsive foot model is considered. The analysis extends previous work on a model with unactuated point feet of Westervelt et al. to include the actuator model of Kuo. The impulsive actuator at each leg end is active only during the double support phase, which results in the model being identical to the model with unactuated point feet for the single support phase. However, the impulsive foot actuation results in a different model for the double support map. Conditions for the existence of a hybrid zero dynamics for the robot with foot actuation are studied. A feedback design method is proposed that integrates actuation in the single and double support phases. A stability analysis is performed using a Poincaré return map. As in Kuo's model, a more efficient gait is demonstrated with an impulsive foot action.

This paper deals with the perception mode of smart wheelchairs. First we evoke the many mobility aid prototypes developed in rehabilitation robotics by considering the point of view of perception. Then we describe the localization mode of the VAHM**. We show how the odometric, ultrasound, and vision sensors are used in a complementary way in order to locate the wheelchair in its known environment. The mode of adjustment of the odometric position by the least-squared method using ultrasonic measurements is detailed. Then the use of vision to perceive the vertical segments of the environment so as to refine the orientation is presented. The results of the tests carried out on the wheelchair are given and commented.

To fully utilize the dynamic performance of robotic manipulators and enforce minimum motion time in path tracking, the problem of minimum time path tracking for robotic manipulators under confined torque, change rate of the torque, and voltage of the DC motor is considered. The main contribution is the introduction of the concepts of virtual change rate of the torque and the virtual voltage, which are linear functions in the state and control variables and are shown to be very tight approximation to the real ones. As a result, the computationally challenging non-convex minimum time path tracking problem is reduced to a convex optimization problem which can be solved efficiently. It is also shown that introducing dynamics constraints can significantly improve the motion precision without costing much in motion time, especially in the case of high speed motion. Extensive simulations are presented to demonstrate the effectiveness of the proposed approach.

In this paper, a development method for smart walker prototypes is proposed. Development of such prototypes is based on technological choices and device evaluations. The method is aimed at guiding technological choices in a modular fashion. First, the method for choosing modules to be integrated in a smart walker is presented. Application-specific modules are then studied. Finally, the issues of evaluation are investigated. In order to work out this method, more than 50 smart walkers and their pros and cons with respect to the different studied applications are reviewed.

This paper presents a comparison between control/state estimation methods applied on Par2 parallel manipulator for pick-and-place applications as well as a discussion about the mechanical vibrations issue that may become important when reaching very high accelerations. Real-time experiments were performed first to compare two controllers (a linear Proportional-Derivative controller and a nonlinear/adaptive Dual Mode (DM) controller) complied with the same High-Gain Observer (HGO) to estimate articular velocities, and second to compare three state observers (a Lead-lag-based, an Alpha-beta-gamma (ABG) and an HGO) complied with the same nonlinear DM controller. The stability analysis of the Par2 robot under the control of the proposed DM controller (complied with the HighGO for joint velocity estimation) is also provided. Some small mechanical vibrations were noted when reaching 20 G acceleration, which means that it can become an important issue for higher accelerations. Some suggestions are then made for future investigations to avoid/damp these vibrations.

The design of multifunctional upper limb prosthetics has been investigated in recent years. In 1998, the MANUS consortium was set up on the basis of multidisciplinary skills of the partners in order to provide a global approach to the problem of upper limb prosthetics. In the framework of this approach, the consortium addressed the development of appropriate hand mechanics, the analysis and implementation of control electronics, the development of advanced control strategies and the implementation of broad band command interfaces based on EMG.

As a result, the prototype of a multifunctional prosthesis was developed, integrated and clinically evaluated. This paper describes the objectives, technological approach and results of the MANUS prosthesis prototype.

The control of a brachiation robot has been the primary objective of this study. A brachiating robot is a type of a mobile arm that is capable of moving from branch to branch similar to a long-armed ape. In this paper, to minimize the actuator work, Pontryagin's minimum principle was used to obtain the optimal trajectories for two different problems. The first problem considers “brachiation between fixed branches with different distance and height,” whereas the second problem deals with the “brachiating and catching of a moving target branch”. Theoretical results show that the control effort in the proposed method is reduced by 25% in comparison with the “target dynamics” method which was proposed by Nakanishi et al. (1998)16 for the same type of robot. As a result, the obtained optimal trajectory also minimizes the brachiation time. Two kinds of controllers, namely the proportional-derivative (PD) and the adaptive robust (AR), were investigated for tracking the proposed trajectories. Then, the previous method on a set-point controller for acrobat robots is improved to represent a new AR controller which allows the system to track the desired trajectory. This new controller has the capability to be used in systems which have uncertainties in the kinematic and dynamic parameters. Finally, theoretical results are presented and validated with experimental observations with a PD controller due to the no chattering phenomenon and small computational efforts.

A method for searching the best location of a path in the robot workspace considering the velocity performance of the robot is presented. After a thorough investigation of the robot performance indices, a new measure for the velocity efficiency of a robot moving its end-effector along a path is introduced. This measure is an approximation of the minimum of the Manipulator Velocity Ratio (MVR) along the path. The minimum is calculated from a finite set of MVRs determined at specified points of the path using an algorithm for an approximate motion of the end effector along the path.

The introduced measure is used as the objective function in an optimisation problem, where an optimal location of the path is searched. The objective function is procedural and non continuous, so a Genetic Algorithm is used to search the space for the optimal location of the path. The proposed method is tested using a simulated PUMA-like robot, which has to move its end-effector along a straight-line segment. At the end of the paper, the results obtained in these tests are presented and discussed.

A crucial problem is the risk that a manipulator arm would be damaged by twisting or bending during and after contacting a target satellite. This paper presents a solution to minimize the risk of damage to the arm and thereby enhance contact performance. First, a hand-eye servo controller is proposed as a method for accurately tracking and capturing a target satellite. Next, a motion planning strategy is employed to obtain the best-fit contacting moments. Also, an impedance control law is implemented to increase protection during operation and to ensure more accurate compliance. Finally, to overcome the challenge of verifying algorithms for a space manipulator while on the ground, a novel experimental system with a 6-DOF (degree of freedom) manipulator on a chaser field robot is presented and implemented to capture a target field robot; the proposed methods are then validated using the experimental platform.

Due to the growing use of Atomic Force Microscope (AFM) nanorobots in the moving and manipulation of cylindrical nanoparticles (carbon nanotubes and nanowires) and the fact that these processes cannot be simultaneously observed, a computer simulation of the involved forces for the purpose of predicting the outcome of the process becomes highly important. So far, no dynamic 3D model that shows changes in these forces in the course of process implementation has been presented. An algorithm is used in this paper to show in 3D, the manner by which the dynamic forces vary in the mentioned process. The presented model can simulate the forces exerted on the probe tip during the manipulation process in three directions. Because of the nonlinearity of the presented dynamic model, the effective parameters have been also studied. To evaluate the results, the parameters of the 3D case (cylindrical model) are gradually reduced and it is transformed into a 2D model (disk model); and we can observe a good agreement between the results of the two simulations. Next, the simulation results are compared with the experimental results, indicating changes in lateral force. With the help of the offered dynamic model, the cantilever deformation and the forces interacting between probe tip and particle can be determined from the moment the probe tip contacts the nanoparticle to when the nanoparticle dislodges from the substrate surface.

Traditionally, tactile sensors have been designed using compliant, rubber-like materials; when such a sensitized gripper grasps or otherwise manipulates an object, the normal strain deformation in the compliant material is sampled. The resulting information can be used to deduce simple local geometry of the contact, but the transduction process does not typically permit use of the individual strains in determining large-scale properties of the object (e.g., the inertia). Measurements of inertial parameters of grasped objects require accurate, low-hysteresis transduction that few tactile sensors currently provide.

An alternative is to work from the task specification, and determine the tactile information that is necessary to accomplish the task. Here, we consider how to sense the length and mass of a uniform object that is gripped in a gravitational field, and show the design and assessment of a new kind of tactile sensor that is based on the theory of the deformation of thin plates. Features of this design include its potentially rugged realization, and its high-accuracy measurement that is more typical of force sensors than of tactile sensors.

A potential panel method is proposed to solve the collision-free pathplanning problem for a free-flying robot operating in an obstacle filled 3-Denvironment. The problem is solved in three steps: (1) transform the arbitraryshaped obstacles in the 3-D workspace into simple convex polyhedrons; (2)generate an artificial potential field using the 3-D panel method in the 3-Dworkspace; (3) generate a streamline from the starting position towards the goalposition in the artificial potential field. The computational complexity of thepertinent algorithms justify the efficiency of the approach and itsapplicability in real-time. Simulation results illustrate the potential of theproposed approach. The reported research is the outgrowth of the 2-D method,already published.