The problem of wheeled mobile robot (WMR) navigation toward an unknown target in a cluttered environment has been considered. The biologically inspired navigation algorithm is the equiangular navigation guidance (ENG) law combined with a local obstacle avoidance technique. The collision avoidance technique uses a system of active sensors which provides the necessary information about obstacles in the vicinity of the robot. In order for the robot to avoid collision and bypass the enroute obstacles, the angle between the instantaneous moving direction of the robot and a reference point on the surface of the obstacle is kept constant. The performance of the navigation strategy is confirmed with computer simulations and experiments with ActivMedia Pioneer 3-DX wheeled robot.

Model-based advanced control approaches are needed to achieve high speed and acceleration and precision in robotic operations. These control schemes need a proper dynamic model. Many approaches have been proposed by different authors in order to obtain the dynamic model of these structures. However, most of them do not consider the possibility to introduce redundant sensor data. In this paper, a methodology for obtaining a compact dynamic model considering passive joint sensor data is proposed. The dynamic model is defined in compact and structured form, which makes it appropriate to be used in advanced control techniques.

This paper describes a landmark detection and localization using an integrated laser-camera sensor. Laser range finder can be used to detect landmarks that are direction invariant in the laser data such as protruding edges in walls, edges of tables, and chairs. When such features are unavailable, the dependant processes will fail to function. However, in many instances, larger number of landmarks can be detected using computer vision. In the proposed method, camera is used to detect landmarks while the location of the landmark is measured by the laser range finder using laser-camera calibration information. Thus, the proposed method exploits the beneficial aspects of each sensor to overcome the disadvantages of the other sensor. While highlighting the drawbacks and limitations of single sensor based methods, an experimental results and important statistics are provided for the verification of the affectiveness sensor fusion method using Extended Kalman Filter (EKF) based simultaneous localization and mapping (SLAM) as an example application.

In this paper, the dynamics and biomimetic control of an artificial finger joint actuated by two opposing one-way shape memory alloy (SMA) muscle wires that are configured in a double spring-biased agonist–antagonist fashion is presented. This actuation system, which was described in Part I, forms the basis for biomimetic tendon-driven flexion/extension and abduction/adduction of the artificial finger. The work presented in this paper centres on thermomechanical modelling of the SMA wire, including both major and minor hysteresis loops in the phase transformation model, and co-operative control strategy of the agonist–antagonist muscle pair using a pulse-width-modulated proportional-integral-derivation (PWM–PID) controller. Parametric analysis and identification are carried out based on both simulation and experimental results. The performance advantage of the proposed co-operative control is shown using the metacarpophalangeal joint of the artificial finger.

This paper presents the research work on a 1 degree of freedom (DOF) force reflecting tele-micromanipulation system. This system enables a human operator to position remote objects very precisely having haptic feedback. The slave robot is a nano-positioning piezo-actuator with hysteretic dynamics. This intrinsic nonlinearity results in positioning inaccuracy and instability. Hence, a LuGre friction model is employed to model and compensate for this undesirable behavior. By means of a transformation, the 2-DOF master–slave system (1-DOF each) is decomposed into two 1-DOF new systems: the shape system, representing the master–slave position coordination, and the locked system, representing dynamics of the coordinated system. A key innovation of this paper is to generalize this approach to the hysteresis-type nonlinear teleoperated systems. For the shape system, a position tracking controller is designed in order to achieve position coordination. This position coordination is guaranteed not only in free space motion, but also during contact at the slave side. Furthermore, a force tracking controller is designed for the locked system in order to achieve tracking of the force exerted on the master and slave robots. Using this force controller, transparency is remarkably enhanced. Based on the virtual flywheels concept, passivity of the closed-loop teleoperator is guaranteed against dynamic parameter uncertainties and force measurement inaccuracies. The simulation and experimental results verify the capability of the proposed control architectures in achieving high-level tracking of the position and force signals while the system remains stable.

The technologies of autonomous rendezvous and robotic capturing of non-cooperative targets are very crucial for the future on-orbital service. In this paper, we proposed a method to achieve this aim. Three problems were addressed: the target recognition and pose (position and attitude) measurement based on the stereo vision, the guidance, navigation and control (GNC) of the chaser, and the coordinated plan and control of space robot (CP&C). The pose measurement algorithm includes image filtering, edge detection, line extraction, stereo match and pose computing, et al. Based on the measured values, a certain GNC algorithm was designed for the chaser to approach and rendezvous with the target. Then the CP&C algorithm, which is proved to be advantageous over the traditional separated method, was used to plan and track the trajectories of the base pose and the joint angle. At last, a 3D simulation system was developed to evaluate the proposed method. Simulation results verified the corresponding algorithms.

In this paper a general methodology for obtaining static stiffness maps in lower mobility parallel manipulators is proposed. The main objective is to define a set of guidelines, which allow the experimental work to be optimized and computational time to be reduced. First, a two-degree-of-freedom (DOF) mechanism will be used for methodology validation, since it is the stiffness of the basic kinematic chain of the manipulator that is to be analysed. Two mathematical models of this mechanism and an experimental prototype will be considered for the validation. After that, the methodology will be applied to a lower mobility (4-DOF) parallel manipulator. In this paper, the experimental prototype and its set-up is highly important because some particular features of the experimental analysis will be defined. This paper introduces a key experimental tool: the preload, which allows the clearances and possible assembling errors to be considered. The added value from the application of this procedure is the obtaining of graphs that describe, in an intuitive and useful way, the behaviour of the manipulator's stiffness inside its workspace as a function of the mobile platform position and orientation.

This paper explores the design of humanoid complicated dynamic motion based on human motion capture. Captured human data must be adapted for the humanoid robot because its kinematics and dynamics mechanisms differ from those of the human actor. It is expected that humanoid movements are highly similar to those of the human actor. First, the kinematics constraints, including ground contact conditions, are formulated. Second, the similarity evaluation on the humanoid motion based on both the spatial and temporal factors compared with the human motion is proposed. Third, the method to obtain humanoid motion with high similarity is presented. Finally, the effectiveness of the proposed method is confirmed by simulations and experiments of our developed humanoid robot “sword” motion performance.

A Jacobian-based algorithm that is useful for planning the motion of a floating rigid body operated using two input torques is addressed in this paper. The rigid body undergoes a four-rotation fully reversed (FR) sequence of rotations which consists of two initial rotations about the axes of a coordinate frame attached to the body and two subsequent rotations that undo the preceding rotations. Although a Jacobian-based algorithm has been useful in exploring the inverse kinematics of conventional robot manipulators, it is not apparent how a correct FR sequence for a desired orientation could be found because the Jacobian of FR sequences is singular as well as being a null matrix at the identity. To discover the FR sequences that can synthesize the desired orientation circumventing these difficulties, the Jacobian algorithm is reformulated and implemented from arbitrary orientations where the Jacobian is not singular. Due to the insufficient degrees-of-freedom of four-rotation FR sequences required to achieve all possible orientations, the rigid body cannot achieve certain orientations in the configuration space. To best approximate these infeasible orientations, the Jacobian-based algorithm is implemented in the sense of least squares. As some orientations can never be attained by a single four-rotation FR sequence, two different four-rotation FR sequences are exploited alternately to ensure the convergence of the proposed algorithm. Assuming the orientation is supposed to be manipulated using three input torques, the switching Jacobian algorithm proposed in this paper has significant practical importance in planning paths for aerospace and underwater vehicles which are maneuvered using only two input torques due to the failure of one of the torque-generation mechanisms.

In this work, we present a continuous observer and continuous controller for a multiple degree of freedom robot manipulator with hysteretic joint friction. The fictitious hysteresis state is of course unknown to the controller and must be estimated. The joint velocities are assumed measured here. For this considered plant, we propose and present a continuous observer/controller that estimates or observes the hysteresis state and drives the position tracking error to zero. We prove that the combined tracking error and observer error converges to zero globally exponentially.

This paper describes a vehicle detection system based on support vector machine (SVM) and monocular vision. The final goal is to provide vehicle-to-vehicle time gap for automatic cruise control (ACC) applications in the framework of intelligent transportation systems (ITS). The challenge is to use a single camera as input, in order to achieve a low cost final system that meets the requirements needed to undertake serial production in automotive industry. The basic feature of the detected objects are first located in the image using vision and then combined with a SVM-based classifier. An intelligent learning approach is proposed in order to better deal with objects variability, illumination conditions, partial occlusions and rotations. A large database containing thousands of object examples extracted from real road scenes has been created for learning purposes. The classifier is trained using SVM in order to be able to classify vehicles, including trucks. In addition, the vehicle detection system described in this paper provides early detection of passing cars and assigns lane to target vehicles. In the paper, we present and discuss the results achieved up to date in real traffic conditions.

In this paper a new approach based on the generalized momentum is used to obtain the dynamic model of a six degrees-of-freedom (dof) parallel manipulator. First, the system dynamic equations are obtained supposing the manipulator base platform is fixed. Afterwards, the dynamic model is extended to the case of a moving base platform. This could be important in a macro/micro robotic application, where a small manipulator is attached in series to a big manipulator. Simulation results of a macro/micro robotic system are presented and the contribution of the base platform motion to the total actuating forces is shown.