Showing papers in "Robotica in 2017"

Uncertainty estimation in robust tracking control of robot manipulators using the Fourier series expansion

Abstract: This paper presents a novel control algorithm for electrically driven robot manipulators. The proposed control law is simple and model-free based on the voltage control strategy with the decentralized structure and only joint position feedback. It works for both repetitive and non-repetitive tasks. Recently, some control approaches based on the uncertainty estimation using the Fourier series have been presented. However, the proper value for the fundamental period duration has been left as an open problem. This paper addresses this issue and intuitively shows that in order to perform repetitive tasks; the least common multiple (LCM) of fundamental period durations of the desired trajectories of the joints is a proper value for the fundamental period duration of the Fourier series expansion. Selecting the LCM results in the least tracking error. Moreover, the truncation error is compensated by the proposed control law to make the tracking error as small as possible. Adaptation laws for determining the Fourier series coefficients are derived according to the stability analysis. The case study is an SCARA robot manipulator driven by permanent magnet DC motors. Simulation results and comparisons with a voltage-based controller using adaptive neuro-fuzzy systems show the effectiveness of the proposed control approach in tracking various periodic trajectories. Moreover, the experimental results on a real SCARA robot manipulator verify the successful practical implementation of the proposed controller.

Motion planning and posture control of multiple n-link doubly nonholonomic manipulators

Abstract: The paper considers the problem of motion planning and posture control of multiple n-link doubly nonholonomic mobile manipulators in an obstacle-cluttered and bounded workspace. The workspace is constrained with the existence of an arbitrary number of fixed obstacles (disks, rods and curves), artificial obstacles and moving obstacles. The coordination of multiple n-link doubly nonholonomic mobile manipulators subjected to such constraints becomes therefore a challenging navigational and steering problem that few papers have considered in the past. Our approach to developing the controllers, which are novel decentralized nonlinear acceleration controllers, is based on a Lyapunov control scheme that is not only intuitively understandable but also allows simple but rigorous development of the controllers. Via the scheme, we showed that the avoidance of all types of obstacles was possible, that the manipulators could reach a neighborhood of their goal and that their final orientation approximated the desired orientation. Computer simulations illustrate these results. KEYWORDS: Lyapunov-based control scheme; Doubly nonholonomic manipulators; Ghost parking bays; Minimum distance technique; Stability; Kinodynamic constraints.

Robust task-space control of robot manipulators using differential equations for uncertainty estimation

Abstract: SUMMARY 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 incremental sampling-based approach to inspection planning: the rapidly exploring random tree of trees

Abstract: 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 3-PRS parallel manipulator for ankle rehabilitation: towards a low-cost robotic rehabilitation

Abstract: This paper presents the design, kinematics, dynamics and control of a low-cost parallel rehabilitation robot developed at the Universitat Politecnica de Valencia. Several position and force controllers have been tested to ensure accurate tracking performances. An orthopedic boot, equipped with a force sensor, has been placed over the platform of the parallel robot to perform exercises for injured ankles. Passive, active-assistive and active-resistive exercises have been implemented to train dorsi/plantar flexion, inversion and eversion ankle movements. In order to implement the controllers, the component-based middleware Orocos has been used with the advantage over other solutions that the whole scheme control can be implemented modularly. These modules are independent and can be configured and reconfigured in both configuration and runtime. This means that no specific knowledge is needed by medical staff, for example, to carry out rehabilitation exercises using this low-cost parallel robot. The integration between Orocos and ROS, with a CAD model displaying the actual position of the rehabilitation robot in real time, makes it possible to develop a teleoperation application. In addition, a teleoperated rehabilitation exercise can be performed by a specialist using a Wiimote (or any other Bluetooth device).

Experimental parameter identification of flexible joint robot manipulators

Abstract: This paper contributes by presenting a parameter identification procedure for n degrees of freedom flexible joint robot manipulators An advantage of the given procedure is the obtaining of robot parameters in a single experiment Guidelines are provided for the computing of the joint position filtering and velocity estimation The method relies in the filtered robot model, for which no acceleration measurements are required The filtered model is expressed in regressor form, which allows applying a parameter identification procedure based on the least squares algorithm In order to assess the performance of the proposed parameter identification scheme, an implementation of a least squares with forgetting factor (LSFF) parameter identification method is carried out In order to assess the reliability of the tested identification schemes, a model based trajectory tracking controller has been implemented twice in different conditions: one control experiment using the estimated parameters provided by the proposed scheme, and another experiment using the parameters given by the LSFF method These real time control experiments are compared with respect to numerical simulations using the estimated parameters for each identification method For the proposed scheme, the comparison between experiments and numerical simulations indicates better accuracy in the torque and position prediction

Motion planning and implementation for the self-recovery of an overturned multi-legged robot

Abstract: 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.

Optimal gait planning for humanoids with 3D structure walking on slippery surfaces

Abstract: 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.

Modeling and control of an underactuated tractor–trailer wheeled mobile robot

Abstract: Trajectory tracking is one of the main control problems in the context of Wheeled Mobile Robots (WMRs). Control of underactuated systems has been focused by many researchers during past few years. In this paper, tracking control of a Tractor–Trailer Wheeled Mobile Robot (TTWMR) has been discussed. TTWMR includes a differential drive WMR towing a passive spherical wheeled trailer. Spherical wheels in contrast with standard wheels make the robot highly underactuated with severe non-linearities. Underactuation is due to the use of spherical wheeled trailer to increase robots' maneuverability and degrees of freedom. In fact, standard wheels are subjected to non-holonomic constraints due to pure rolling and non-slip conditions, which reduce robot maneuverability. In this paper, after introducing the robot, kinematics and kinetics models are obtained. Then, based on a physical intuition, a novel control algorithm is developed for the robot, i.e. Lyapunov-PID control algorithm. Subsequently, singularity avoidance of the proposed algorithm is discussed and the stability of the algorithm is analyzed. Finally, simulation and experimental results are presented which reveal the effectiveness of the proposed algorithm.

Collision-free workspace of parallel mechanisms based on an interval analysis approach

Abstract: 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.

Multi-Contact Bipedal Robotic Locomotion

Abstract: This paper presents a formal framework for achieving multi-contact bipedal robotic walking, and realizes this methodology experimentally on two robotic platforms: AMBER2 and Assume The Robot Is A Sphere (ATRIAS). Inspired by the key feature encoded in human walking—multi-contact behavior—this approach begins with the analysis of human locomotion and uses it to motivate the construction of a hybrid system model representing a multi-contact robotic walking gait. Human-inspired outputs are extracted from reference locomotion data to characterize the human model or the spring-loaded invert pendulum (SLIP) model, and then employed to develop the human-inspired control and an optimization problem that yields stable multi-domain walking. Through a trajectory reconstruction strategy motivated by the process that generates the walking gait, the mathematical constructions are successfully translated to the two physical robots experimentally.

Efficient motion generation for a six-legged robot walking on irregular terrain via integrated foothold selection and optimization-based whole-body planning

Abstract: In this paper, an efficient motion planning method is proposed for a six-legged robot walking on irregular terrain. The method provides the robot with fast-generated free-gait motions to traverse the terrain with medium irregularities. We first of all introduce our six-legged robot with legs in parallel mechanism. After that, we decompose the motion planning problem into two main steps: first is the foothold selection based on a local footstep cost map, in which both terrain features and the robot mobility are considered; second is a whole-body configuration planner which casts the problem into a general convex optimization problem. Such decomposition reduces the complexity of the motion planning problem. Along with the two-step planner, discussions are also given in terms of the robot-environmental relationship, convexity of constraints and robot rotation integration. Both simulations and experiments are carried out on typical irregular terrains. The results demonstrate effectiveness of the planning method.

A distributed control algorithm for area search by a multi-robot team

Abstract: In this paper, we present a novel algorithm for exploring an unknown environment using a team of mobile robots. The suggested algorithm is a grid-based search method that utilizes a triangular pattern which covers an area so that exploring the whole area is guaranteed. The proposed algorithm consists of two stages. In the first stage, all the members of the team make a common triangular grid of which they are located on the vertices. In the second stage, they start exploring the area by moving between vertices of the grid. Furthermore, it is assumed that the communication range of the robots is limited, and the algorithm is based on the information of the nearest neighbours of the robots. Moreover, we apply a new mapping method employed by robots during the search operation. A mathematically rigorous proof of convergence with probability 1 of the algorithm is given. Moreover, our algorithm is implemented and simulated using a simulator of the real robots and environment and also tested via experiments with Adept Pioneer 3DX wheeled mobile robots.

Closed form Newton–Euler dynamic model of flexible manipulators

Abstract: In this paper, a closed-form dynamic model of flexible manipulators is developed, based on the Newton–Euler formulation of motion equations of flexible links and on the adoption of the spatial vector notation. The proposed model accounts for two main innovations with respect to the state of the art: it is obtained in closed form with respect to the joints and modal coordinates (including the quadratic velocity terms) and motion equations of the whole manipulator can be computed for any arbitrary shape of the links and any possible link cardinality starting from the output of several commercial (finite element analysis) FEA codes. The Newton–Euler formulation of motion equations in terms of the joint and elastic variables greatly improves the simulation performances and makes the model suitable for real-time control and active vibration damping. The model has been compared with literature benchmarks obtained by the classical multibody approach and further validated by comparison with experiments collected on an experimental manipulator.

Kinematic model to control the end-effector of a continuum robot for multi-axis processing

Abstract: This paper presents a novel kinematic approach for controlling the end-effector of a continuum robot for in-situ repair/inspection in restricted and hazardous environments. Forward and inverse kinematic (IK) models have been developed to control the last segment of the continuum robot for performing multi-axis processing tasks using the last six Degrees of Freedom (DoF). The forward kinematics (FK) is proposed using a combination of Euler angle representation and homogeneous matrices. Due to the redundancy of the system, different constraints are proposed to solve the IK for different cases; therefore, the IK model is solved for bending and direction angles between (−π/2 to +π/2) radians. In addition, a novel method to calculate the Jacobian matrix is proposed for this type of hyper-redundant kinematics. The error between the results calculated using the proposed Jacobian algorithm and using the partial derivative equations of the FK map (with respect to linear and angular velocity) is evaluated. The error between the two models is found to be insignificant, thus, the Jacobian is validated as a method of calculating the IK for six DoF.

Modelling the temperature in joint friction of industrial manipulators

Abstract: In this paper, a new model for joint dynamic friction of industrial robot manipulators is presented. In particular, the effects of the temperature in the joints are considered. A polynomial-based model is proposed and the parameter estimation is performed without the need of a joint temperature sensor. The use of an observer is then proposed to compensate for the uncertainty in the initial estimation of the temperature value. A large experimental campaign show that the model, in spite of the simplifying assumptions made, is effective in estimating the joint temperature and therefore the friction torque during the robot operations, even for values of velocities that have not been previously employed.

Three-dimensional tracking control of autonomous underwater vehicles with limited torque and without velocity sensors

Abstract: Most of the previous works on the motion control of autonomous underwater vehicles (AUVs) assume that (i) the vehicle actuators are able to tolerate every level of the control signals, and (ii) the vehicle is equipped with the velocity sensors in all degrees of freedom. These assumptions are not desirable in practice. Toward this end, this paper addresses the trajectory tracking control of the underactuated AUVs with the limited torque, without the velocity measurements and under environmental disturbances in a three-dimensional space. At first, a variable transformation is introduced which helps us to derive a second-order dynamic model for underactuated AUVs. Then, a saturated tracking controller is proposed by employing the saturation functions to bound the closed-loop error variables. This technique reduces the risk of the actuators saturation by decreasing the amplitude of the generated control signals. In addition, a nonlinear saturated observer is introduced to remove the velocity sensors from the control system. The proposed controller copes with the uncertain vehicle parameters, and constant or time-varying environmental disturbances induced by the waves and ocean currents. Lyapunov's direct method is used to show the semi-global uniform ultimate boundedness of the tracking and state estimation errors. Finally, some simulation results illustrate the effectiveness of the proposed controller.

An approach for real-time motion planning of an inchworm robot in complex steel bridge environments

Abstract: Path planning can be difficult and time consuming for inchworm robots especially when operating in complex 3D environments such as steel bridges. Confined areas may prevent a robot from extensively searching the environment by limiting its mobility. An approach for real-time path planning is presented. This approach first uses the concept of line-of-sight (LoS) to find waypoints from the start pose to the end node. It then plans smooth, collision-free motion for a robot to move between waypoints using a 3D-F2 algorithm. Extensive simulations and experiments are conducted in 2D and 3D scenarios to verify the approach.

Autonomous Multirobot Excavation for Lunar Applications

Abstract: In this paper, a control approach called Artificial Neural Tissue (ANT) is applied to multirobot excavation for lunar base preparation tasks including clearing landing pads and burying of habitat modules. We show for the first time, a team of autonomous robots excavating a terrain to match a given three-dimensional (3D) blueprint. Constructing mounds around landing pads will provide physical shielding from debris during launch/landing. Burying a human habitat modules under 0.5 m of lunar regolith is expected to provide both radiation shielding and maintain temperatures of −25 °C. This minimizes base life-support complexity and reduces launch mass. ANT is compelling for a lunar mission because it does not require a team of astronauts for excavation and it requires minimal supervision. The robot teams are shown to autonomously interpret blueprints, excavate and prepare sites for a lunar base. Because little pre-programmed knowledge is provided, the controllers discover creative techniques. ANT evolves techniques such as slot-dozing that would otherwise require excavation experts. This is critical in making an excavation mission feasible when it is prohibitively expensive to send astronauts. The controllers evolve elaborate negotiation behaviors to work in close quarters. These and other techniques such as concurrent evolution of the controller and team size are shown to tackle problem of antagonism, when too many robots interfere reducing the overall efficiency or worse, resulting in gridlock. Although many challenges remain with this technology, our work shows a compelling pathway for field testing this approach.

A comparative study of in-field motion capture approaches for body kinematics measurement in construction

Abstract: Due to physically demanding tasks in construction, workers are exposed to significant safety and health risks. Measuring and evaluating body kinematics while performing tasks helps to identify the fundamental causes of excessive physical demands, enabling practitioners to implement appropriate interventions to reduce them. Recently, non-invasive or minimally invasive motion capture approaches such as vision-based motion capture systems and angular measurement sensors have emerged, which can be used for in-field kinematics measurements, minimally interfering with on-going work. Given that these approaches have pros and cons for kinematic measurement due to adopted sensors and algorithms, an in-depth understanding of the performance of each approach will support better decisions for their adoption in construction. With this background, the authors evaluate the performance of vision-based (RGB-D sensor-, stereovision camera-, and multiple camera-based) and an angular measurement sensor-based (i.e., an optical encoder) approach to measure body angles through experimental testing. Specifically, measured body angles from these approaches were compared with the ones obtained from a marker-based motion capture system that has less than 0.1 mm of errors. The results showed that vision-based approaches have about 5–10 degrees of error in body angles, while an angular measurement sensor-based approach measured body angles with about 3 degrees of error during diverse tasks. The results indicate that, in general, these approaches can be applicable for diverse ergonomic methods to identify potential safety and health risks, such as rough postural assessment, time and motion study or trajectory analysis where some errors in motion data would not significantly sacrifice their reliability. Combined with relatively accurate angular measurement sensors, vision-based motion capture approaches also have great potential to enable us to perform in-depth physical demand analysis such as biomechanical analysis that requires full-body motion data, even though further improvement of accuracy is necessary. Additionally, understanding of body kinematics of workers would enable ergonomic mechanical design for automated machines and assistive robots that helps to reduce physical demands while supporting workers' capabilities.

Smart walkers: an application-oriented review

Abstract: In this paper, a development method for smart walker prototypes is proposed. Development of such prototypes is based on technological choices and device evaluations. The method is aimed at guiding technological choices in a modular fashion. First, the method for choosing modules to be integrated in a smart walker is presented. Application-specific modules are then studied. Finally, the issues of evaluation are investigated. In order to work out this method, more than 50 smart walkers and their pros and cons with respect to the different studied applications are reviewed.

Integral terminal sliding mode formation control of non-holonomic robots using leader follower approach

Abstract: Multi-robot formation control has become an important area of research due to its advantages and applications. This paper presents multi-robot formation control using a leader–follower approach without considering the leader's velocity information or estimation. The leader–follower formation is formulated by incorporating the model uncertainties and disturbances. A novel formation controller is presented using integral terminal sliding mode (ITSM) control, which drives the formation tracking error convergence to zero in finite-time. The stability of the close-loop control scheme is verified by using Lyapunov theory. Furthermore, obstacle detection and avoidance are incorporated to avoid collision while maintaining the formation. The effectiveness of the proposed controller is verified and validated using sine and lamniscate curve trajectories. Moreover, the performance of the proposed ITSM formation controller is compared with the standard linear sliding mode (LSM) control.

Cascaded control for balancing an inverted pendulum on a flying quadrotor

Abstract: This paper is focused on the flying inverted pendulum problem, i.e., how to balance a pendulum on a flying quadrotor. After analyzing the system dynamics, a three loop cascade control strategy is proposed based on active disturbance rejection control (ADRC). Both the pendulum balancing and the trajectory tracking of the flying quadrotor are implemented by using the proposed control strategy. A simulation platform of 3D mechanical systems is deployed to verify the control performance and robustness of the proposed strategy, including a comparison with a Linear Quadratic Controller (LQR). Finally, a real quadrotor is flying with a pendulum to demonstrate the proposed method that can keep the system at equilibrium and show strong robustness against disturbances.

Model validation of a hexapod walker robot

Abstract: Our complete dynamical simulation-model realistically describes the real low-cost hexapod walker robot Szabad(ka)-II within prescribed tolerances under nominal load conditions. This validated model is novel, described in detail, for it includes in a single study: (a) digital controllers, (b) gearheads and DC motors, (c) 3D kinematics and dynamics of 18 Degree of Freedom (DOF) structure, (d) ground contact for even ground, (e) sensors and battery model. In our model validation: (a) kinematical-, dynamical- and digital controller variables were simultaneously compared, (b) differences of measured and simulated curves were quantified and qualified, (c) unknown model parameters were estimated by comparing real measurements with simulation results and applying adequate optimization procedures. The model validation helps identifying both model's and real robot's imperfections: (a) gearlash of the joints, (b) imperfection of approximate ground contact model, (c) lack of gearhead's internal non-linear friction in the model. Modeling and model validation resulted in more stable robot which performed better than its predecessors in terms of locomotion.

Fault tolerance properties and motion planning of a six-legged robot with multiple faults

Abstract: The six-legged robot Octopus is designed for nuclear disaster relief missions. When the robot suffers from failures, its performance can be significantly affected. Thus, fault tolerance is essential for walking and operating in environments inaccessible to humans. The current fault-tolerant gaits for legged robots usually either initially lock the entire broken leg or just abandon the broken leg, but then fail to take full advantage of the normal actuators on the broken leg and add extra constraints. As the number of broken legs increases, the robot will no longer be able to walk using the existing fault-tolerant gaits. To solve this problem, screw theory is used for analyzing the remaining mobility after failure. Based on the analysis, a method of motion planning through fault-tolerant Jacobian matrices, which are linear, is presented. This method can enable the robot to accomplish desired movement using broken legs along with other certain concomitant motions as compensation. Finally, experiments and simulations of multiple faults demonstrate the real effects on the Octopus robot.

Pick and place trajectory planning of planar 3-RRR parallel manipulator in the presence of joint clearance

Abstract: In this paper, the pick and place trajectory planning of a planar 3-RRR parallel manipulator is studied in the presence of joint clearance, which is one of the main sources of error in the positioning accuracy. Joint clearance can be modeled as a massless virtual link, with its direction determined from dynamic analysis. A 3–4–5 interpolating polynomial is used to plan the trajectories for the manipulator in the vertical and horizontal planes, in the presence of clearances. We compare the trajectories with those in the ideal cases, i.e., without clearances at the joints, and demonstrate that one can easily compensate for the errors in the trajectories by appropriate changes of the inputs. A similar method works for the compensation of the errors due to clearances at the joints, in trajectory planning of any parallel manipulator with any running speeds and payloads.

Development, design and validation of an assistive device for hand disabilities based on an innovative mechanism

Abstract: In accordance with strict requirements of portability, cheapness, and modularity, an innovative assistive device for hand disabilities has been developed and validated. This robotic orthosis is designed to be a low-cost, portable hand exoskeleton to assist people with physical disabilities in their everyday lives. Referring to hand opening disabilities, the authors have developed a methodology which, by starting from the geometrical characteristics of the patient's hand, defines the novel kinematic mechanism that better fits to the finger trajectories. The authors have validated the proposed novel mechanism by carrying out a Hand Exoskeleton System (HES) prototype, based on a single-phalanx mechanism, cable driven. The testing phase of the real prototype with a patient is currently on going.

Observer-based two-time scale robust control of free-flying flexible-joint space manipulators with external disturbances

Abstract: 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.

Sit-to-stand and stand-to-sit assistance for paraplegic patients with CUHK-EXO exoskeleton

Abstract: In this paper, we introduce a lower extremity exoskeleton CUHK-EXO that is developed to help paraplegic patients, who have lost the motor and sensory functions of their lower limbs to perform basic daily life motions. Since the sit-to-stand and stand-to-sit (STS) motion is the first step for paraplegic patients toward walking, analysis of the exoskeleton's applicability to the STS motion assistance is performed. First, the human-exoskeleton system (HES) is modeled as a five-link model during the STS motion, and the center of pressure (COP) on the ground and center of gravity of the whole system are calculated. Then, a description of the CUHK-EXO hardware design is presented, including the mechatronics design and actuator selection. The COP position is an important factor indicating system balance and wearer's comfort. Based on the COP position, a trajectory online modification algorithm (TOMA) is proposed for CUHK-EXO to counteract disturbances, stabilize system balance, and improve the wearer's comfort in the STS motion. The results of STS motion tests conducted with a paraplegic patient demonstrate that CUHK-EXO can provide a normal reference pattern and proper assistive torque to support the patient's STS motion. In addition, a pilot study is conducted with a healthy subject to verify the effectiveness of the proposed TOMA under external disturbances before future clinical trials. The testing results verify that CUHK-EXO can counteract disturbances, and help the wearer perform the STS motion safely and comfortably.

Robust adaptive control for robot manipulators: Support vector regression-based command filtered adaptive backstepping approach

Abstract: This study derives a robust adaptive control of electrically driven robot manipulators using a support vector regression (SVR)-based command filtered adaptive backstepping approach. The robot system is supposed to be subject to model uncertainties, neglected dynamics, and external disturbances. The command filtered backstepping algorithm is extended to the case of the robot manipulators. A robust term is added to the common adaptive SVR algorithm, to mitigate the effects of the SVR approximation error in the path tracking performance. The stability analysis of the closed loop system using the Lyapunov theory permits to highlight adaptation laws and to prove that all the signals in the closed loop system are bounded. Simulations show the effectiveness of the proposed control strategy.