A multimodal actuator was proposed to achieve a more agile power-assisted exoskeleton in uncertain complex walking environments. A power-assisted knee exoskeleton prototype based on a multimodal actuator was constructed. With this multimodal actuator, several modes of operation in the power-assisted knee exoskeleton during a motion cycle are actuated, including series elastic actuation, stiff position control, and energy storage and release. Also, a control strategy for power-assisted knee exoskeleton motion control based on a state machine is developed. The ability of the power-assisted knee exoskeleton to follow human motion was tested, and the results showed that the angle error of the knee exoskeleton followed the human motion is not more than 0.4˚, and the response time error of the knee exoskeleton followed the human motion is not more than 0.2 s.

This paper proposes an interval-based approach in order to obtain the obstacle-free workspace of parallel mechanisms containing one prismatic actuated joint per limb, which connects the base to the end-effector. This approach is represented through two cases studies, namely a 3-RPR planar parallel mechanism and the so-called 6-DOF Gough–Stewart platform. Three main features of the obstacle-free workspace are taken into account: mechanical stroke of actuators, collision between limbs and obstacles and limb interference. In this paper, a circle(planar case)/spherical(spatial case) shaped obstacle is considered and its mechanical interference with limbs and edges of the end-effector is analyzed. It should be noted that considering a circle/spherical shape would not degrade the generality of the problem, since any kind of obstacle could be replaced by its circumscribed circle/sphere. Two illustrative examples are given to highlight the contributions of the paper.

We present an analytical method for the concurrent calculation of optimal parallel compliant elements and frequency of reference trajectories for serial manipulators performing cyclic tasks. In this approach, we simultaneously shape and exploit the robot's natural dynamics by finding a set of compliant elements and task frequency that result in minimization of an energy-based cost function. The cost function is the integral of a weighted squared norm of the generalized forces. We prove that the generalized force needed for tracking the reference trajectory is a linear function of compliance coefficients and a quadratic function of task frequency. Therefore, the cost function is quadratic with respect to stiffness coefficients and quartic with respect to the task frequency. These properties lead to a well-posed optimization problem with a closed-form solution. Using three case studies, we elucidate the properties of our method.

We give a full classification of all pentapods with linear platform possessing a self-motion beside the trivial rotation about the platform. Recent research necessitates a contemporary and accurate re-examination of old results on this topic given by Darboux, Mannheim, Duporcq and Bricard, which also takes the coincidence of platform anchor points into account. For our study we use bond theory with respect to a novel kinematic mapping for pentapods with linear platform, beside the method of singular-invariant leg-rearrangements. Based on our results we design pentapods with linear platform, which have a simplified direct kinematics concerning their number of (real) solutions.

In this study, a gait optimization routine is developed to generate walking patterns which demand the lowest friction forces for implementation. The aim of this research is to fully address the question “which walking pattern demands the lowest coefficient of friction amongst all feasible patterns?”. To this end, first, the kinematic structure of the considered 31 DOF (Degrees of Freedom) humanoid robot is investigated and a closed-form dynamics model for its lower-body is developed. Then, the medium through which the walking pattern generation is conducted is presented. In this medium, after designing trajectories for the feet and the pelvis, the joint space variables are obtained, using the inverse kinematics. Finally, by employing a genetic algorithm (GA), an optimization process is conducted to generate walking patterns with the minimum Required Coefficient Of Friction (RCOF). Six parameters are adopted to parameterize the pelvis trajectory and are exploited as the design variables in this optimization procedure. Also, a parametrical study is accomplished to address the effects of some other variables on RCOF. For comparison purposes, a tip-over Stability Margin (SM) is defined, and an optimization procedure is conducted to maximize this margin. Finally, the proposed gait planning procedure is implemented on SURENA III, a humanoid robot designed and fabricated in CAST, to validate the developed simulation procedure. The obtained results reveal merits of the proposed optimal gait planning procedure in terms of RCOF.

This paper first presents a method of motion planning and implementation for the self-recovery of an overturned six-legged robot. Previous studies aimed at the static and dynamic stabilization of robots for preventing them from overturning. However, no one can guarantee that an overturn accident will not occur during various applications of robots. Therefore, the problems involving overturning should be considered and solved during robot design and control. The design inspirations of multi-legged robots come from nature, especially insects and mammals. In addition, the self-recovery approach of an insect could also be imitated by robots. In this paper, such a self-recovery mechanism is reported. The inertial forces of the dangling legs are used to bias some legs to touch the ground, and the ground reaction forces exerted on the feet of landing legs are achieved to support and push the body to enable recovery without additional help. By employing the mechanism, a self-recovery approach named SSR (Sidewise-Self-Recovery) is presented and applied to multi-legged robots. Experiments of NOROS are performed to validate the effectiveness of the self-recovery motions. The results show that the SSR is a suitable method for multi-legged robots and that the hemisphere shell of robots can help them to perform self-recovery.

A new algorithm, called rapidly exploring random tree of trees (RRTOT) is proposed, that aims to address the challenge of planning for autonomous structural inspection. Given a representation of a structure, a visibility model of an onboard sensor, an initial robot configuration and constraints, RRTOT computes inspection paths that provide full coverage. Sampling based techniques and a meta-tree structure consisting of multiple RRT* trees are employed to find admissible paths with decreasing cost. Using this approach, RRTOT does not suffer from the limitations of strategies that separate the inspection path planning problem into that of finding the minimum set of observation points and only afterwards compute the best possible path among them. Analysis is provided on the capability of RRTOT to find admissible solutions that, in the limit case, approach the optimal one. The algorithm is evaluated in both simulation and experimental studies. An unmanned rotorcraft equipped with a vision sensor was utilized as the experimental platform and validation of the achieved inspection properties was performed using 3D reconstruction techniques.

A hyper-redundant manipulator is made by mounting the serial and/or parallel mechanisms on top of each other as modules. In discrete actuation, the actuation amounts are a limited number of certain values. It is not feasible to solve the kinematic analysis problems of discretely actuated hyper-redundant manipulators (DAHMs) by using the common methods, which are used for continuous actuated manipulators. In this paper, a new method is proposed to solve the trajectory tracking problem in a static prescribed obstacle field. To date, this problem has not been considered in the literature. The removing first collision (RFC) method, which is originally proposed for solving the inverse kinematic problems in the obstacle fields was modified and used to solve the motion planning problem. For verification, the numerical results of the proposed method were compared with the results of the genetic algorithm (GA) method. Furthermore, a novel DAHM designed and implemented by the authors is introduced.

This paper presents an adaptive distributed control strategy for n-serial-flexible-link manipulators. The proposed adaptive controller is used for flexible-link-manipulators: (1) to solve the tracking control problem in the joint space, and (2) to reduce vibrations of the links. The dynamical model of flexible link manipulators is reorganized to take the form of n interconnected subsystems. Each subsystem has a one-joint and one-link pair. The system parameters are deemed to be unknown. The adaptive distributed strategy controls one subsystem in each step, starting from the last one. The nth subsystem is controlled by assuming that the remaining subsystems are stable. Then, proceeding backward to the (n-1)th system, the same strategy is applied, and so on, until the first subsystem is reached. The gradient-based estimator is used to estimate the parameters of each subsystem. The control law of the ith subsystem uses its own estimated parameters and the estimated parameters of all upper level subsystems. The global stability of the error dynamics is proved using Lyapunov approach. This algorithm was implemented in real time on a two-flexible-link manipulator, and a comparison with the non-adaptive version shows the effectiveness of this approach.

Multi-level manipulators are those mechanisms in which two or more levels, that define the main chain of the manipulator, are joined in parallel to each other. Besides, each level is linked to the base in parallel by some limbs. Based on the idea of multi-level manipulators and using the concept of plain leg surfaces, the synthesis of partially decoupled manipulators with five degrees of freedom is presented. Among the different possibilities that exist to design the main chain of the manipulator, one is selected and the different manipulators that can be obtained from this option are analyzed. The concept of control distribution per level is presented and compared with the distribution of degrees of freedom per level. Finally, each of the proposed manipulators is studied and those which decouple the rotations are chosen.

Observer-based two-time scale robust control is proposed for free-flying flexible-joint space manipulators with unknown payload parameters and bounded disturbances. The dynamic equations of a free-flying space manipulator with two flexible revolute joints were derived by the momentum conservation law and the Lagrange equations. A flexibility compensator was introduced to make the equivalent joint stiffness large enough, which made traditional singular perturbation approach applicable. Then, a singular perturbation model was formulated and a reduced-order controller is proposed. This controller consisted of a slow sub-controller and a fast flexible-joint sub-controller. To the slow subsystem, a sliding observer based robust slow sub-controller was proposed. By optimal linear quadratic regulator method, the fast sub-controller was designed with the estimated velocity by linear observer. This fast sub-controller could stabilize the fast subsystem around the equilibrium trajectory created by the slow subsystem under the effect of the slow control. Finally the numerical simulations were carried out, which showed that elastic joint vibrations had been stabilized effectively and good tracking performances had been achieved.

In this paper, design, analysis and real-time trajectory tracking control of a 6-degree of freedom revolute spherical-spherical type parallel manipulator, actuated by six hybrid stepper motors, has been studied. Two different control approaches have been used to improve the trajectory tracking performance of the designed manipulator. The first approach considered a single input-single output (SISO) linear quadratic regulator (LQR) for trajectory tracking control of the manipulator. Another controller type based on a nonlinear sliding mode controller method has been utilized to take decoupled dynamic approximation model of the manipulator into account and to improve tracking performance of the manipulator. Real-time experimental results for the two different control techniques have been verified. Finally, according to the results, the nonlinear sliding mode controller method has improved the tracking performance of the designed manipulator.

Robotic hands use rolling contact to manipulate a grasped object to a desired location, even when the finger and the palm linkage mechanisms lack degrees of freedom. This paper presents a systematic approach to the forward and inverse kinematics of in-hand manipulation. The moving frame method in differential geometry is integrated into the product of exponential formula to establish a pure geometric framework of the kinematics of a robot hand. The forward and inverse kinematics of a multifingered hand are obtained in terms of the joint rates and contact trajectories. A two-fingered planar robot hand and a three-fingered spatial robot hand are used to demonstrate the proposed approach. The proposed formulation amounts to solving a univariate polynomial, providing an alternative to the existing ones that require numerical integration.

Because space manipulators must satisfy the law of conservation of momentum, any motion of a manipulator within a space-manipulator system disturbs the position and attitude of its free-floating base. In this study, the authors have designed a multi-swarm particle swarm optimization (PSO) algorithm to address the motion planning problem and so minimize base disturbances for 6-DOF space manipulators. First, the equation of kinematics for space manipulators in the form of a generalized Jacobian matrix (GJM) is introduced. Second, sinusoidal and polynomial functions are used to parameterize joint motion, and a quaternion representation is used to represent the attitude of the base. Moreover, by transforming the planning problem into an optimization problem, the objective function is analyzed and the proposed algorithm explained in detail. Finally, numerical simulation results are used to verify the validity of the proposed algorithm.

In this study, a bilateral teleoperation control algorithm is developed in which the model-mediation method is integrated with an impedance controller. The model-mediation method is also extended to three-degrees-of-freedom teleoperation. The aim of this controller is to compensate for instability issues and excessive forcing applied to the slave environment stemming from time delays in communication. The proposed control method is experimentally tested with two haptic desktop devices. Test results indicate that stability and passivity of the bilateral teleoperation system is preserved under variable time delays in communication. It is also observed that safer interactions of the slave system with its environment can be achieved by utilizing an extended version of the model-mediation method with an impedance controller.

Optimization is an important step in the design and development of a planar parallel manipulator. For optimization processes, workspace analysis is a crucial and preliminary objective. Generally, the workspace analysis for such manipulators is carried out using a non-dimensional approach. For planar parallel manipulators of two degrees of freedom (2-DOF), a non-dimensional workspace analysis is very advantageous. However, it becomes very difficult in the case of 3-DOF and higher DOF manipulators because of the complex shape of the workspace. In this study, the workspace shape is classified as a function of the geometric parameters, and the closed-form area expressions are derived for a constant orientation workspace of a three revolute–revolute–revolute (3-RRR) planar manipulator. The approach is also shown to be feasible for different orientations of a mobile platform. An optimization procedure for the design of planar 3-RRR manipulators is proposed for a prescribed workspace area. It is observed that the closed-form area expression for all the possible shapes of the workspace provides a larger solution space, which is further optimized considering singularity, mass of the manipulator, and a force transmission index.

The main innovation of this paper is determining the dynamic load carrying capacity (DLCC) of a flexible joint manipulator (FJM) using a closed form nonlinear optimal control approach. The proposed method is compared with two closed loop nonlinear methods that are usually applied to robotic systems. As a new idea, DLCC of the manipulator is considered as a criterion to compare how well controllers perform point to point mission for the FJMs. The proposed method is compared with feedback linearization (FL) and robust sliding mode control (SMC) methods to show better performance of proposed nonlinear optimal control approach. An optimal controller is designed by solving a nonlinear partial differential equation named the Hamilton–Jacobi–Bellman (HJB) equation. This equation is complicated to solve exactly for complex dynamics so it is solved numerically using an iterative approximation combined with the Galerkin method. In the FL method, angular position, velocity, acceleration and jerk of links are considered as new states to linearize the dynamic equations. In the case of SMC, the dynamic equations of manipulator are changed to the standard form then the Slotine method is used to design the sliding mode controller. Two simulations are performed for a planar and a spatial Puma manipulator and performances of controllers are compared. Finally an experimental test is done on 6R manipulator and the Stereo vision method is used to determine the position and orientation of the end-effector.

Most control algorithms for rigid-link electrically driven robots are given in joint coordinates. However, since the task to be accomplished is expressed in Cartesian coordinates, inverse kinematics has to be computed in order to implement the control law. Alternatively, one can develop the necessary theory directly in workspace coordinates. This has the disadvantage of a more complex robot model. In this paper, a robust control scheme is given to achieve exact Cartesian tracking without the knowledge of the manipulator kinematics and dynamics, actuator dynamics and nor computing inverse kinematics. The control design procedure is based on a new form of universal approximation theory and using Stone–Weierstrass theorem, to mitigate structured and unstructured uncertainties associated with external disturbances and actuated manipulator dynamics. It has been assumed that the lumped uncertainty can be modeled by linear differential equations. As the method is Model-Free, a broad range of manipulators can be controlled. Numerical case studies are developed for an industrial robot manipulator.

An effective algorithm for path planning is introduced based on a novel concept, the distorted configuration space (DC-space), where all obstacles deform into dimensionless geometric objects. Path planning in this space can be conducted by simply connecting the starting position and ending position with a straight line. This linear path in the DC-space is then mapped back into a feasible in the original C-space. The advantage of this approach is that no trial-and-error or iteration is needed while a feasible path can be found directly if it exists. An algorithm with general formulas is derived. Examples in 2D and 3D are provided to validate this concept and algorithm.

Designing and testing flight control algorithms for quadrotor UAVs (unmanned aerial vehicles) is not an easy task due to the risk of possible danger and damage during the practical flight. In order to improve the safety and efficiency of the flight control implementation, a low-cost real-time HILS (hardware-in-the-loop simulation) testbed for quadrotor UAVs is developed in this paper. To realize the HILS testbed, a miniature quadrotor is used as the main body, equipped with a micro AHRS (attitude heading reference system) unit and a self-build DSP (digital signal processor) board. The HILS is implemented by using xPC target. A compact PC/104 computer is utilized as the target computer, and a laptop PC is employed as the host computer. A desktop PC is used as flight visualization computer which runs FlightGear and Google Earth to show visual data, such as orientation and flight path of the quadrotor UAV. This testbed can be utilized for simulating various flight control algorithms, without losing safeness and reliableness. To demonstrate the effectiveness of the proposed testbed, a new nonlinear adaptive sliding mode based stabilization control algorithm is developed and verified on the HILS testbed.