An efficient method for tracking a target using a single Pan-Tilt-Zoom (PTZ) camera is proposed. The proposed Scale-Invariant Optical Flow (SIOF) method estimates the motion of the target and rotates the camera accordingly to keep the target at the center of the image. Also, SIOF estimates the scale of the target and changes the focal length relatively to adjust the Field of View (FoV) and keep the target appear in the same size in all captured frames. SIOF is a feature-based tracking method. Feature points used are extracted and tracked using Optical Flow (OF) and Scale-Invariant Feature Transform (SIFT). They are combined in groups and used to achieve robust tracking. The feature points in these groups are used within a twist model to recover the 3D free motion of the target. The merits of this proposed method are (i) building an efficient scale-invariant tracking method that tracks the target and keep it in the FoV of the camera with the same size, and (ii) using tracking with prediction and correction to speed up the PTZ control and achieve smooth camera control. Experimental results were performed on online video streams and validated the efficiency of the proposed method SIOF, comparing with OF, SIFT, and other tracking methods. The proposed SIOF has around 36% less average tracking error and around 70% less tracking overshoot than OF.

This paper presents recent results and applications of our planar kinematic synthesis of serial and parallel linkages to guide a rigid body, such that it does not violate normal direction and curvature constraints imposed by contact with objects in the environment. The paper briefly reviews the recently developed theory on transforming contact direction and curvature constraints into conditions on velocity and acceleration of certain points in the moving body to obtain synthesis equations which can, subsequently be solved to find the dimensions of a mechanical linkage. The main contribution of the paper is in demonstrating the applicability of the proposed theory to the kinematic synthesis of both open and closed-loop kinematic linkages. We provide preliminary results on the synthesis of kinematic chains based on novel task specifications that incorporate curvature constraints with a variety of applications, such as passive suspensions for small rovers, assistive technologies, as well as grasping.

This paper presents a concept of a laser scanner framework designed for obstacle avoidance used on mini fixed-wing unmanned aerial vehicles (UAVs) flying in outdoor environments. The innovation is a conical field of view that guarantees tri-dimensional (3D) obstacle detection and localization at any pitch or roll angle. This advantage is very important for the case of fixed-wing UAV flights where the attitude is changing rapidly. Measurement sequences create a map that is represented by a circular grid with the center fitted to the x-axis of the UAV's body, lying in the plane normal to the velocity vector and projected in the front of UAV. This means that the map cells contain differences between the safety zone radius and distances acquired from area in close proximity to the flight path. Actual UAV attitude can be compensated by rotation and shift of two masks of gains that are applied to the map to determine pitch and roll commands. Results of the simulation research conducted on the designed concept are very promising, as they present a combination of lateral and vertical obstacle avoidance. Based on the experience with laser rangefinders operating on a real UAV, it can be convincingly determined that the concept of the laser scanner is able to be brought into reality.

This paper presents a systematic approach to compute the angularity and the axiality indices for a Schönflies parallel manipulator. Angularity index may be considered as a measure of the sensitivity of the mobile platform to changes in rotation, while axiality index can be used to measure the sensitivity of the OP of the mobile platform to changes in translation. Since both indices were inspired by very fundamental concepts of classical kinematics (angular velocity vector and helicoidal velocity field), they offer a clear and simple physical meaning, which may be useful to the designer of parallel manipulators. Moreover, both dexterity indices do not require obtaining a dimensionally homogeneous Jacobian matrix, nor do they depend on having similar types of actuators in each manipulator's leg. Detailed numerical examples are given in order to illustrate the computation of the dexterity indices.

This paper establishes a novel approach of robotic hand posture and grasping control. For this purpose, the control uses the operational space approach. This permits the consideration of the shape of the object to be grasped. Thus, the control is split into a task control and a particular optimizing posture control. The task controller employs Cylindrical and Spherical coordinate systems due to their simplicity and geometric suitability. This is achieved by using an integral sliding mode controller (ISMC) as task controller. The ISMC allows us to introduce a model reference approach where a virtual mass-spring-damper system can be used to design a compliant trajectory tracking controller. The optimizing posture controller together with the task controller creates a simple approach to obtain pre-grasping/object approach hand postures. The experimental results show that target trajectories can be easily followed by the task control despite the presence of friction and stiction. When the object is grasped, the compliant control will automatically adjust to a specific compliance level due to an augmented compliance parameter adjustment algorithm. Once a specific compliance model has been achieved, the fixed compliance controller can be tested for a specific object grasp scenario. The experimental results prove that the Bristol Elumotion robot hand (BERUL) can automatically and successfully attain different compliance levels for a particular object via the ISMC.

The goal of this study is to investigate the use of emotion as a braking system for wheelchair navigation. In the first part emotion is detected based on ElectroEncephalography (EEG) technology and emotion induction experiments. Using different techniques for features extraction (Welch and Wavelets), selection (Principal Component Analysis (PCA) and Genetic Algorithm (GA)) and classification (Support Vector Machine (SVM), Multi Layer Perceptron (MLP) and Linear Discriminate Analysis (LDA)), the best combination was assigned to Wavelets-GA-MLP. In the second part, in order to validate the impact of emotion as velocity modulator, a comparison between emotion-based and non emotion-based wheelchair navigation scenarios in a simulated environment was conducted. The assessment was based on four parameters: obstacles hit, navigation path, execution time and outbound points of gaze (POG). While the first two emotion introductions showed better results, this was not the case for the third. These findings can be utilized in order to prescribe a suitable wheelchair according to the subject pathology.

A flexible apple sorting hand-claw with three fingers evenly on the spiral chuck is designed. Each finger with series double hinges is driven by one air-cylinder. Sizes of hand-claw and parameters of two torsion springs round axes of series double hinges are obtained via global optimization based on the grid method so that the two torsion springs exhibit a coordinative function to enhance compliance for grasping apples of different sizes under the same system pressure. Besides, the critical pressures and bending deflection between different working processes are studied. Results show that hinge 2 begins to rotate at 0.0270 MPa pressure, and when the pressure increases to 0.0634 MPa and 0.0746 MPa, hand-claw begins to touch the biggest and the smallest apples respectively. The curve of torsional angle versus pressure presents that angular velocity droops with homogeneous extension. Therefore, it is able to reduce impact and time in vain during the grasping process. Crucially, the grasping forces for grasping the smallest and the biggest apple are 4 N and 4.38 N respectively under the same 0.5 MPa pressure, indicating the excellent adaption performance and robust result for size variation of apples without any force sensors.

Biped walking can be regarded as a global limit cycle whose stability is difficult to verify by only local sensory feedback. This paper presents a control strategy combining global sensory reflex and leg synchronization. The inverted pendulum angle is utilized as global motion feedback to ensure global stability, and joint synchronization between legs is designed to stabilize bifurcations. The proposed strategy can achieve a stable gait and stabilize bifurcations. The robustness of this approach was evaluated against external disturbances. Walking experiments of a biped actuated by pneumatic muscles were conducted to confirm the validity of the proposed method. Instead of tracking predetermined trajectories, this method uses sensory reflexes to activate motor neurons and coincides with the biological idea wherein inessential degrees-of-freedom are barely controlled rather than strictly controlled.

Passive walking robots can walk on a slight downward slope powered only by gravity. We propose a novel control strategy based on forced entrainment to stabilize a three-dimensional quasi-passive walking robot in uphill and level walking by using torso control in the frontal plane and synchronization of lateral motion with swing leg motion. We investigated the robot's walking energy efficiency, energy transformation, and transfer in simulation. The results showed that the proposed method is effective and energy-efficient for uphill and level walking. The relationship between energy utilization rate of actuation and energy efficiency of the robot was revealed, and mechanical energy transformation and transfer were characterized.

In this paper, a fast and efficient evolutional algorithm, called the G3-PCX has been implemented to solve the forward kinematics problem (FKP) of the general parallel manipulators being modeled by the 6-6 hexapod, constituted by a fixed and mobile platforms being non planar and non-symmetrical. The two platforms are connected by six linear actuators, each of which is located between one ball joint and one universal joint. Forward kinematics are formulated using Inverse Kinematics applying one position based equation system which is converted into an objective function by expressing the sum of squared error on kinematics chain lengths and mobile platform distances. In less than one second, the 16 unique real solutions are computed with improved accuracy when compared to previous methods.

This paper presents a new observer-based adaptive controller for handling an object with unknown geometry, center of mass, and inertia using a cooperative robotic system. The cooperative robotic system comprises three Cartesian robots, where robots and the grasped object form a closed-loop kinematic chain. The unknown object is approximated by three virtual links of unknown lengths rigidly attached to one another at the object's center of mass (COM). Due to the unknown COM and unknown inertia of the object, the lengths and inertia of these virtual links are unknown, resulting in kinematic and dynamic uncertainties in the control system. A parameter estimator is proposed to estimate the object's COM to compensate for kinematic uncertainties of the system. Moreover, a new dynamic adaptation law is developed to cope with dynamic uncertainties of the object. The dynamic equations of the cooperative system are transformed from joint space into task space. These task space dynamics are transformed into object space by passively decomposing the dynamics into two decoupled systems, i.e. locked and shaped systems. An adaptive controller is developed for the locked system, and the shaped system is controlled by a composite controller based on a PD controller plus a stabilizing damping term. The stability of the proposed controllers is shown using the passivity concept and Lyapunov theorem. Simulation results show that the closed-loop position error asymptotically converges to zero. It is also shown that kinematic and dynamic adaptation parameters converge to real and bounded values respectively.

Molecular biological systems can be seen as extremely complex mobile systems. The development of methods for modeling the structure and the motion of such systems is essential to better understand their physiochemical properties and biological functions. In recent years, many computer scientists in robotics and artificial intelligence have made significant contributions to modeling biological systems. Research expertise in planning, search, learning, evolutionary computation, constraint programming, and data mining is being used to make great progress on molecular motion, structure prediction, and design.

This paper presents design, modelling and analysis of the selected Rigid ropes S-type Cable-suspended Parallel Robot (RSCPR). The characteristic of this system is its geometric construction which defines the kinematic model through the Jacobian matrix. The relationship between external and internal forces is defined by the Lagrange principle of virtual work. The Jacobian matrix is directly involved in the application of the Lagrange principle of virtual work and generation of the dynamic model of the RSCPR system. Selected examples of the CPR system types are analysed and the comparison of their results is presented. The software package named ORIGI has been developed for the RSCPR model verification.

In this paper, the problem of obtaining the optimal trajectory of a Dual-Arm Cam-Lock (DACL) robot is addressed. The DACL robot is a reconfigurable manipulator consisting of two cooperative arms, which may act separately. These may also be cam-locked in each other in some links and thus lose some degrees of freedom while gaining higher structural stiffness. This will also decrease their workspace volume. It is aimed to obtain the optimal configuration of the robot and the optimal joint trajectories to minimize the consumed energy for following a specific task space path. The Pontryagin's Minimum Principle is utilized with a shooting method to resolve kinematic redundancy. Numerical examples are investigated to show optimal trajectories in different cam-locked configurations, and the final decision is made based on a selection table of the computed performance indices.

A new robust neural sliding mode (RNSM) tracking control scheme using radial basis function (RBF) neural network (NN) is presented for MEMS z-axis gyroscope to achieve robustness and asymptotic tracking error convergence. An adaptive RBF NN controller is developed to approximate and compensate the large uncertain system dynamics, and a robust compensator is designed to eliminate the impact of NN modeling error and external disturbances for guaranteeing the asymptotic stability property. Moreover, another RBF NN is employed to learn the upper bound of NN modeling error and external disturbances, so the prior knowledge of the upper bound of system uncertainties is not required. All the adaptive laws in the RNSM control system are derived in the same Lyapunov framework, which can guarantee the stability of the closed loop system. Comparative numerical simulations for an MEMS gyroscope are investigated to verify the effectiveness of the proposed RNSM tracking control scheme.

Researchers dream of developing autonomous humanoid robots which behave/walk like a human being. Biped robots, although complex, have the greatest potential for use in human-centred environments such as the home or office. Studying biped robots is also important for understanding human locomotion and improving control strategies for prosthetic and orthotic limbs. Control systems of humans walking in cluttered environments are complex, however, and may involve multiple local controllers and commands from the cerebellum. Although biped robots have been of interest over the last four decades, no unified stability/balance criterion adopted for stabilization of miscellaneous walking/running modes of biped robots has so far been available. The literature is scattered and it is difficult to construct a unified background for the balance strategies of biped motion. The zero-moment point (ZMP) criterion, however, is a conservative indicator of stabilized motion for a class of biped robots. Therefore, we offer a systematic presentation of multi-level balance controllers for stabilization and balance recovery of ZMP-based humanoid robots.

The workspace is often a critical parameter for optimum design of parallel manipulators. Workspace shape and area are two important considerations under this. In this paper, 5-R and 3-RRR planar parallel manipulators having symmetric link lengths are considered for workspace analysis. Here, symmetric means that the lengths of the first and second links of the legs are the same in all branches. Workspace analysis for such manipulators is normally done in a nondimensional way. The determination of the workspace area is one of the important parameters in the optimum design of a manipulator, and the determination of the area in terms of nondimensional parameters is extremely difficult in the case of 3-DOF and higher-DOF manipulators. In this paper, a geometric method is presented to determine different workspace shapes and areas. Based on this, all possible shapes of workspace are presented for both 5-R and 3-RRR planar parallel manipulators. For each case, a geometrical relationship between the link lengths is determined. The geometric approach gives a closed-form expression for the area calculation, which is not possible when adopting a nondimensional approach. In addition, this approach provides relationships between workspace shape and area and link lengths.

An S-R-S (Spherical-Revolute-Spherical) redundant manipulator is similar to a human arm and is often used to perform dexterous tasks. To solve the inverse kinematics analytically, the arm-angle was usually used to parameterise the self-motion. However, the previous studies have had shortcomings; some methods cannot avoid algorithm singularity and some are unsuitable for configuration control because they use a temporary reference plane. In this paper, we propose a method of analytical inverse kinematics resolution based on dual arm-angle parameterisation. By making use of two orthogonal vectors to define two absolute reference planes, we obtain two arm angles that satisfy a specific condition. The algorithm singularity problem is avoided because there is always at least one arm angle to represent the redundancy. The dual arm angle method overcomes the shortcomings of traditional methods and retains the advantages of the arm angle. Another contribution of this paper is the derivation of the absolute reference attitude matrix, which is the key to the resolution of analytical inverse kinematics but has not been previously addressed. The simulation results for typical cases that include the algorithm singularity condition verified our method.

Molecular replacement (MR) is a well-established computational method for phasing in macromolecular crystallography. In MR searches, spaces of motions are explored for determining the appropriate placement of rigid single-body (or articulated multi-rigid-body) models of macromolecules. By determining a priori which portions of motion space correspond to non-physical packing arrangements with symmetry mates in collision, it becomes feasible to construct more efficient MR techniques which avoid searching in these non-realizable regions of motion space. This paper investigates which portion of the motion space is physically realizable, given that packing of protein molecules in a crystal are subject to the constraint that they cannot interpenetrate, and gives explicit expressions for the volume of the non-realizable regions for crystals in two-dimensions.

This paper proposes a novel three-degrees-of-freedom (3-DOF) hybrid manipulator, 3PU*S-PU, which evolves from the general function (Gf) set theory. After discussing the advantages of this new type of hybrid manipulator, this report analyzes the kinematic and Jacobian matrix of the manipulator. Subsequently, the kinematic performances, including stiffness/compliance, and workspace, undergo analysis, followed by the multi-objective optimization of the compliance and workspace. The Lagrangian method provides the framework for briefly analyzing the dynamics of the proposed manipulator. Finally, the results of this assessment comprise a guideline for controlling the manipulator.