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.

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.

Due to the special working environment of teleoperation, there are usually uncertainties existing in the dynamics of teleoperating robots. In this paper, an adaptive bilateral control scheme is proposed for the nonlinear teleoperation with parameterized dynamic uncertainties and time delays. Compared to the existing time-delay adaptive bilateral controllers, the proposed scheme has the advantage of faster and more accurate parameter adaptation. In this way, the transient performance of teleoperators can be improved without increasing the control gains, which is helpful for stability of teleoperation. The adaptive bilateral controller is designed to be applicable both in free motion and in constrained motion. The synchronization errors in the unconstrained subspace are asymptotically convergent under time delays. In the constrained subspace, the contact force remains bounded with the proposed controller. The stability of teleoperation is proved using Lyapunov methods and the passivity theory. Simulation results demonstrate the effectiveness of the proposed method.

In this paper a motion planner for nonholonomic stratified systems was proposed. Those systems may arise easily when reliable systems are designed to be robust against failures in difficult servicing environments. For a special class of the systems, a strong controllability condition was introduced, and a criterion to satisfy the condition was formulated and used to plan the motion of free-floating space manipulators. Modules of the planner were enumerated and their roles were emphasized. Some features of the planner were examined and discussed based on simulation results performed on two models of space manipulators.

This paper introduces a novel 6-DOF parallel manipulator, which is composed of two 3-RUS parallel manipulators that share a common three-dimensional moving platform. Semi-analytical form solutions are easily obtained to solve the forward displacement analysis of the robot using the non-planar geometry of the moving platform, whereas the velocity, acceleration, and singularity analyses are performed using screw theory. A case study is included to show the application of the kinematic model, which is verified with the aid of a commercially available software. Simple kinematic analysis and reduced singular regions are the main benefits of the proposed parallel manipulator.

This paper presents a new solution approach for managing the motion of a fleet of autonomous vehicles (AVs) in indoor factory environments. AVs are requested to serve a number of workstations (WS) (following a specified desired production plan for materials requirements) while taking into account the safe movement (collisions avoidance) in the shop floor as well as time duration and energy resources. The proposed approach is based on the Bump-Surface concept to represent the 2D environment through a single mathematical entity. The solution of the combined problem of path planning and task scheduling is searched on a higher-dimension B-surface (in our case 3D) in such a way that its inverse image into the robot environment satisfies the given objectives and constraints. Then, a modified Genetic Algorithm (GA) is used to search for a near-optimum solution. The objective of the fleet coordination consists of determining the best feasible paths for the AVs so that all the WS are served at the lowest possible cost. The efficiency of the developed method is investigated and discussed through characteristic simulated experiments concerning a variety of operating environments.

Real-time responses for multiple robots motion planning demand heuristic algorithms. This paper presents a method to evaluate the efficiency of these algorithms in order to compute coordinated trajectories for multiple car-like robots on a segment of a highway. The idea is to compare the results of these algorithms with the optimal result obtained by a proposed mixed-integer linear programming (MILP) optimization model. The MILP model considers the main elements of a traffic system, such as topography of lanes, traffic rules and individual capacity of acceleration. Moreover, new indexes for microscopic traffic assessment are proposed a well. Several tests have been carried out to validate both the MILP model and the algorithm used.

In this paper, we propose a biomechatronic design of an anthropomorphic artificial hand that is able to mimic the natural motion of human fingers. The prosthetic hand has 5 fingers and 15 joints, which are actuated by 5 embedded motors. Each finger has three phalanges that can fulfill flexion-extension movements independently. The thumb is specially designed to move along a cone surface when grasping, and the other four fingers are well developed based on the four-bar link mechanism to imitate the motion of the human finger. To accomplish the sophisticated control schemes, the fingers are equipped with numerous torque and position sensors. The mechanical parts, sensors, and motion control systems are integrated in the hand structure, and the motion of the hand can be controlled through electromyography (EMG) signals in real-time. A new concept for the sensory feedback system based on an electrical stimulator is also taken into account. The low-cost prosthetic hand is small in size (85% of the human hand), of low weight (420 g) and has a large grasp power (10 N on the fingertips), hence it has a dexterous and humanlike appearance. The performance of the prosthetic hand is validated in a clinical evaluation on transradial amputees.

In this study, a general kinematic control law for automatic multi-configuration of four-wheel active drive/steer robots is proposed. This work presents models of four-wheel drive and steer (4WD4S) robotic systems with all-wheel active drive and steer simultaneously. This kinematic model comprises 12 degrees of freedom (DOFs) in a special design of a mechanical structure for each wheel. The control variables are wheel yaw, wheel roll, and suspension pitch by active/passive damper systems. The pitch angle implies that a wheel's contact point translates its position over time collinear with the robot's lateral sides. The formulation proposed involves the inference of the virtual z-turn axis (robot's body rotation axis) to be used in the control of the robot's posture by at least two acceleration measurements local to the robot's body. The z-turn axis is deduced through a set of linear equations in which the number of equations is equal to the number of acceleration measurements. This research provides two main models for stability conditions. Finally, the results are sustained by different numerical simulations that validate the system with different locomotion configurations.

In this paper, a robust adaptive fuzzy controller is proposed to improve the robustness and position tracking of a MEMS gyroscope sensor. The proposed controller is designed as an indirect adaptive fuzzy controller with a supervisory compensator. It incorporates a fuzzy inference system with an adaptive controller in a unified Lyapunov framework, which can approximate and compensate for the unknown system dynamics and nonlinearities in the MEMS gyroscope. The parameters of the membership functions in the fuzzy controller can be adjusted online based on the Lyapunov method. Moreover, a supervisory controller is employed to guarantee the asymptotic stability of the closed-loop system and boundedness of the state variables in the MEMS gyroscope model. Numerical simulations demonstrate the proposed robust adaptive fuzzy controller has satisfactory tracking performance and robustness in the presence of external disturbances.

An underactuated mechanical system is generally a good test bed for advanced nonlinear controllers and can be applied to design a novel mechanical system with better energy efficiency and good controllability. It has been shown that the dynamics of many underactuated mechanical systems could be transformed into the chained canonical form. To improve the performance of the controllers presented in the literature, a novel controller design method is proposed in this paper. It is shown that the set-point stabilization problem of the second-order chained form systems can be changed into a trajectory-tracking problem based on the nonsmooth Hölder continuous feedback. By designing the tracked trajectory, the presented controller permits the achievement of exponential stability. Some numerical simulations demonstrate the stability of the proposed controller for an underactuated Hovercraft system.

This paper deals with the stiffness analysis of multibody systems using the Matrix Structural Analysis—MSA. This methodology allows us to obtain the stiffness matrix of the structure from the stiffness properties of each element. First the MSA method is described and its application is detailed using an L-structure in order to make easy its understanding. Numerical and experimental results obtained for the L-structure and a 6-RSS parallel manipulator, follow to prove the validity of the methodology.

A novel n(2-UPS/PS+RPS) spatial hyper-redundant manipulator (SHRM) formed by an optional number of 2-UPS/PS+RPS(2-universal joint-prismatic joint-spherical joint/prismatic joint-spherical joint+revolute joint-prismatic joint-spherical joint) parallel manipulators(PMs) connected in series is proposed and analyzed in this paper. First, the forward kinematics of the 2-UPS/PS+RPS PM is derived in close form. By extending this result to the whole SHRM, the forward kinematics model of the n(2-UPS/PS+RPS) SHRM is established. Second, the compact and elegant expressions for solving the forward velocity of the n(2-UPS/PS+RPS) SHRM are derived. Third, the statics and stiffness of the n(2-UPS/PS+RPS) SHRM are analyzed systematically by considering both active forces and constrained forces existed in each 2-UPS/PS+RPS PM. Finally, an analytically solved example is given for a 4(2-UPS/PS+RPS) SHRM formed by four 2-UPS/PS+RPS PMs. The analytical results are verified by CAD software.

In the context of topological mapping, the automatic segmentation of an environment into meaningful and distinct locations is still regarded as an open problem. This paper presents an algorithm to extract places online from image sequences based on the algebraic connectivity of graphs or Fiedler value, which provides an insight into how well connected several consecutive observations are. The main contribution of the proposed method is that it is a theoretically supported alternative to tuning thresholds on similarities, which is a difficult task and environment dependent. It can accommodate any type of feature detector and matching procedure, as it only requires non-negative similarities as input, and is therefore able to deal with descriptors of variable length, to which statistical techniques are difficult to apply. The method has been validated in an office environment using exclusively visual information. Two different types of features, a bag-of-words model built from scale invariant feature transform (SIFT) keypoints, and a more complex fingerprint based on vertical lines, color histograms, and a few Star keypoints, are employed to demonstrate that the method can be applied to both fixed and variable length descriptors with similar results.