In this paper, the kinematics and dynamics of a parallel manipulator with a new architecture supposed to be used as a moving mechanism in a flight simulator project is studied. This manipulator with three independent degrees of freedom consists of a moving platform connected to a based platform by means of three legs. Kinematic solutions for this manipulator at position, velocity and acceleration levels are obtained. Moreover, the dynamical equations of motion of the manipulator are determined using Newton-Euler's equations and applying the natural orthogonal complement (NOC) method. Using kinematics and dynamics and also performing simulation for different manoeuvres of moving platform, the motion and the actuator forces of the legs are obtained.

The 3 degree-of-freedom Gantry-Tau manipulator with the addition of the spherical wrist mechanism which is called Gantry-Tau-3R is designed as a high-G simulation-based motion platform (SBMP) with the capability of generating the large linear and angular displacement. The combination of both parallel and serial manipulator in newly designed Gantry-Tau-3R mechanism improves the ability of the mechanism to regenerate larger motion signals with higher linear acceleration and angular velocity. The high-frequency signals are reproduced using the parallel part of the mechanism, and sustainable low-frequency accelerations are regenerated via the serial part due to the larger rotational motion capability, which will be used through motion cueing algorithm tilt coordination channel. The proportional integral derivative (PID) and fuzzy incremental controller (FIC) are developed for the proposed mechanism to show the high path tracking performance as a motion platform. FIC reduces the motion tracking error of the newly designed Gantry-Tau-3R and increases the motion fidelity for the users of the proposed SBMP. The proposed method is implemented using Matlab/Simulink software. Finally, the results demonstrate the accurate motion signal generation using linear model predictive motion cues with a fuzzy controller, which is not possible using the common parallel and serial manipulators.

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.

In this paper, tip tracking control of a single-link flexible robot is studied through computer simulations. The controller investigated is of a two-loop PD type, which is deduced from a control approach originally developed for elastic joint robots. A very simple model, with the flexible link of the robot being lumped to a spring-mass unit, is employed for the controller design. Bounded Input and Bounded Output (BIBO) stable tip tracking performance is guaranteed. The controller is robustly stable under system parameter uncertainties, and is comparatively easy to implement. In the simulations, different payloads are considered, and the system performance is compared with the traditional Singular Perturbation (SP) method. The simulation results show that the PD type controller designed based on the simple lumped model is able to provide quite satisfactory performance.

We investigated and identified the conditions necessary for stable dynamic gait generation in biped robots from the mechanical energy balance point of view. The equilibrium point at impact in a dynamic gait is uniquely determined by two conditions; keeping the restored mechanical energy constant and settling the relative hip-joint angle to the desired value before impact. The generated gait then becomes asymptotically stable around the equilibrium point determined by these conditions. This is shown by a simple recurrence formula of the kinetic energy immediately before impact. We verified this stability theorem using numerical simulation of virtual passive dynamic walking. The results were compared with those for a rimless wheel and an inherent stability principle was derived. Finally, we derived a robust control law using a reference mechanical energy trajectory and demonstrated its effectiveness numerically.

In this paper, we investigate the problem of measuring the shape of a continuum robot manipulator using visual information from a fixed camera. Specifically, we capture the motion of a set of fictitious planes, each formed by four or more feature points, defined at various strategic locations along the body of the robot. Then, utilizing expressions for the robot forward kinematics as well as the decomposition of a homography relating a reference image of the robot to the actual robot image, we obtain the three-dimensional shape information continuously. We then use this information to demonstrate the development of a kinematic controller to regulate the manipulator end-effector to a constant desired position and orientation.

In this paper, motion synchronization is investigated for human–robot collaboration such that the robot is able to “actively” follow its human partner. Force tracking is achieved with the proposed method under the impedance control framework, subject to uncertain human limb dynamics. Adaptive control is developed to deal with point-to-point movement, and learning control and neural networks control are developed to generate periodic and arbitrary continuous trajectories, respectively. Stability and tracking performance of the closed-loop system are discussed through rigorous analysis. The validity of the proposed method is verified through simulation and experiment studies.

This paper exploits a natural symmetry present in a 3D robot in order to achieve asymptotically stable steering. The robot under study is composed of 5-links and unactuated point feet; it has 9 DoF (degree-of-freedom) in the single-support phase and six actuators. The control design begins with a hybrid feedback controller that stabilizes a straight-line walking gait for the 3D bipedal robot. The closed-loop system (i.e., robot plus controller) is shown to be equivariant under yaw rotations, and this property is used to construct a modification of the controller that has a local, but uniform, input-to-state stability (ISS) property, where the input is the desired turning direction. The resulting controller is capable of adjusting the net yaw rotation of the robot over a step in order to steer the robot along paths with mild curvature. An interesting feature of this work is that one is able to control the robot's motion along a curved path using only a single predefined periodic motion.

The design of the robotic mechanisms is most important because they determine the performance characteristics of the robots. This paper concerns the issue of computer-aided design (CAD) for planar 3-DOF parallel robotic mechanisms by means of the physical model of the solution space, which can be used systematically to express the relationships between the performance criteria and all link lengths of one type of the robtic mechanism. The performance atlases of the workspace volume for the manipulators are plotted in the physical model of the solution space. The characteristics of the distribution of the workspace shapes in the physical model of the solution space are presented. The results are useful for the optimum design of the robotic mechanisms. This paper proposes a new way for robotic CAD.

This paper approaches the design problem of suitable grippers for a robotic arm to pick up horticulture products. General considerations have been pointed out and main concepts and mechanical designs have been discussed and proposed by sketches and drawings for an easy understanding of “on-field” problems and feasible solutions. Pneumatic actuation has been proposed with suitable grasp force control by using commercial components. Specific attention has been focused on tomato horticulture for a practical design and prototyping of a device for laboratory experiments.

In this paper, accuracy and stiffness analysis of a 3-RRP spherical parallel manipulator (SPM) (Enferadi and Tootoonchi, A novel spherical parallel manipulator: Forward position problem, singularity analysis and isotropy design, Robotica, vol. 27, 2009, pp. 663–676) with symmetrical geometry is investigated. At first, the 3-RRP SPM is introduced and its inverse kinematics analysis is performed. Isotropic design, because of its design superiority, is selected and workspace of the manipulator is obtained. The kinematics conditioning index (KCI) is evaluated on the workspace. Global conditioning index (GCI) of the manipulator is calculated and compared with another SPM. Unlike traditional stiffness analysis, the moving platform is assumed to be flexible. A continuous method is used for obtaining mathematical model of the manipulator stiffness matrix. This method is based on strain energy and Castigliano's theorem. The mathematical model is verified by finite element model. Finally, using mathematical model, kinematics stiffness index (KSI), and global stiffness index (GSI) are evaluated.

At Imperial College, the author has invented a form of universal gripper comprising two slightly separated ‘fingers’, each consisting of an array of 8 by 16 closely spaced pins which can ride vertically up and down independently of each other. Lowering the gripper over an object pushes some pins out of the way, so creating ‘customised’ fingers which mould round and fit the part. To grasp objects, either the two (slightly separated) fingers can be brought together to grip an object externally, or else they can be moved slightly apart (from a ‘closed’ position) for an internal grip. In addition, feedback from each pin of the gripper can provide tactile information about an object.

This paper presents a novel one-degree-of-freedom (1-DOF) single-loop reconfigurable 7R mechanism with multiple operation modes (SLR7RMMOM), composed of seven revolute (R) joints, via adding a revolute joint to the overconstrained Sarrus linkage. The SLR7RMMOM can switch from one operation mode to another without disconnection and reassembly, and is a non-overconstrained mechanism. The algorithm for the inverse kinematics of the serial 6R mechanism using kinematic mapping is adopted to deal with the kinematic analysis of the SLR7RMMOM. First, a numerical method is applied and an example is given to show that there are 13 sets of solutions for the SLR7RMMOM, corresponding to each input angle. Among these solutions, nine sets are real solutions, which are verified using both a computer-aided design (CAD) model and a prototype of the mechanism. Then an algebraic approach is also used to analyse the mechanism and same results are obtained as the numerical one. It is shown from both numerical and algebraic approaches that the SLR7RMMOM has three operation modes: a translational mode and two 1-DOF planar modes. The transitional configurations among the three modes are also identified.

This paper presents a new approach for the design of variable structure control (VSC) of nonlinear systems. The approach is based on estimation of joint acceleration signals with introduction of load estimation with the asymptotic observer. The control system is insensitive to parameter variations for a chosen switching hypersurface in conditions when it is reached by the dynamic motion with the required dynamics. The parameter insensitive response provided by this control method is demonstrated on the model of the SCARA robot. Simulation results confirm the validity of accurate tracking capability and the robust performance.

In this paper, we propose a method of using an autonomous flying robot to explore an underground tunnel environment and build a 3D map. The robot model we use is an extension of a 2D non-holonomic robot. The measurements and sensors we considered in the presented method are simple and valid in practical unmanned aerial vehicle (UAV) engineering. The proposed safe exploration algorithm belongs to a class of probabilistic area search, and with a mathematical proof, the performance of the algorithm is analysed. Based on the algorithm, we also propose a sliding control law to apply the algorithm to a real quadcopter in experiments. In the presented experiment, we use a DJI Guidance sensing system and an Intel depth camera to complete the localization, obstacle detection and 3D environment information capture. Furthermore, the simulations show that the algorithm can be implemented in sloping tunnels and with multiple UAVs.

Space robotic systems are expected to play an increasingly important role in the future. Unlike on the earth, space operations require the ability to work in the unstructured environment. Some autonomous behaviors are necessary to perform complex and difficult tasks in space. This level of autonomy relies not only on vision, force, torque, and tactile sensors, but also the advanced planning and decision capabilities. In this paper, the authors study the autonomous target capturing from the issues of theory and experiments. Firstly, we deduce the kinematic and dynamic equations of space robotic system. Secondly, the visual measurement model of hand–eye camera is created, and the image processing algorithms to extract the target features are introduced. Thirdly, we propose an autonomous trajectory planning method, directly using the 2D image features. The method predicts the target motion, plans the end-effector's velocities and solves the inverse kinematic equations using practical approach to avoid the dynamic singularities. At last, numeric simulation and experiment results are given. The ground experiment system is set up based on the concept of dynamic simulation and kinematic equivalence. With the system, the experiments of autonomous capturing a target by a free-floating space robot, composed of a 6-DOF manipulator and a satellite as its base, are conducted, and the results validate the proposed algorithm.

This paper describes current progress in a project to develop robotic systems for locating underground chemical sources. There are a number of economic and humanitarian applications for this technology. Finding unexploded ordinance, land mines, and sources of leaks from pipes and tanks are some examples. Initial experiments were conducted using an ethanol chemical source buried in coarse sand. To gain an understanding of the sensory environment that would be experienced by a robot burrowing through the ground, the factors affecting transport of chemical vapour through soil were investigated. A robot search algorithrn was then developed for gathering chemical gradient inforrnation and using this to guide a robot towards the source. Experiments were performed using a chemical sensing probe positioned by a UMI RTX robot manipulator arm. The resulting system was successful in locating a source of ethanol vapour buried in sand. This paper includes details of experiments to characterise the sand used in this project, the robot search algorithm, sensor probe and results of source location trials.

This paper presents an architecture for the navigation of an autonomous mobile robot evolving in environments with obstacles. Instead of addressing the motion planning and control problems in different contexts, these issues are described in connected modules with performance requirement considerations. The path planning problem is formulated as a constrained receding horizon planning problem and is solved in real time with an efficient computational method that combines non-linear control theory, B-spline basis function and non-linear programming. An integral sliding mode controller is used for trajectory tracking. The closed-loop stability of the tracking errors is guaranteed in spite of unknown disturbances. It is also shown that this strategy is particularly useful if integral sliding mode control is combined with other methods to further robustify against perturbations. The effectiveness, perfect performance of obstacle avoidance, real time and high robustness properties are demonstrated by experimental results.

This paper presents a new approach to matching occupancy grid maps by means of finding correspondences between a set of sparse features detected in the maps. The problem is stated here as a special instance of generic image registration. To cope with the uncertainty and ambiguity that arise from matching grid maps, we introduce a modified RANSAC algorithm which searches for a dynamic number of internally consistent subsets of feature pairings from which to compute hypotheses about the translation and rotation between the maps. By providing a (possibly multi-modal) probability distribution of the relative pose of the maps, our method can be seamlessly integrated into large-scale mapping frameworks for mobile robots. This paper provides a benchmarking of different detectors and descriptors, along extensive experimental results that illustrate the robustness of the algorithm with a 97% success ratio in loop-closure detection for ~1700 matchings between local maps obtained from four publicly available datasets.