Legged robots may become unstable when subjected to unexpected disturbances such as external pushes and environmental irregularities mostly while moving on natural terrains. To enhance the mobility performance, legged robots should be able to keep or restore their balanced configuration when a sudden disturbance is exerted. The aim of this article is to design a controller for a quadruped robot to restore its balanced configuration despite exerting external pushes. This is achieved based on developing a full-dynamics model of the robot moving over even and uneven terrains. The proposed controller is based on a PD module which calculates the required accelerations for restoring the robot equilibrium. However, these accelerations may make the robot unstable and also cause the slippage of stance feet. Therefore, an optimization algorithm is used to compute the maximum admissible accelerations. The constraints of the optimization problem are the conditions which guarantee the robot stability and the stance feet slippage avoidance. The optimization algorithm is transformed into a linear constrained least-squares problem to be solved in real-time. The main contributions of this article are the development of a push recovery algorithm for quadruped robots and also the introduction of an appropriate condition which guarantees the stability of the robot even on uneven terrains. This stability condition is developed based on a full-dynamics model of the robot. The proposed algorithm is applied on an 18-DOF quadruped robot when the robot is standing over both even and uneven terrains. The obtained results show that the robot can successfully restore its balanced configuration by precise adjustment of the position and orientation of its main body while a massive external disturbance is exerted.

This paper focuses on fast terminal sliding mode control (FTSMC) of robot manipulators using wavelet neural networks (WNN) with guaranteed H∞ tracking performance. The FTSMC for trajectory tracking is employed to drive the tracking error of the system to converge to an equilibrium point in finite time. The tracking error arrives at the sliding surface in finite time and then converges to zero in finite time along the sliding surface. To deal with the case of uncertain and unknown robot dynamics, a WNN is proposed to fully compensate the robot dynamics. The online tuning algorithms for the WNN parameters are derived using Lyapunov approach. To attenuate the effect of approximation errors to a prescribed level, H∞ tracking performance is proposed. It is shown that the proposed WNN is able to learn the system dynamics with guaranteed H∞ tracking performance and finite time convergence for trajectory tracking. Finally, the simulation results are performed on a 3D-Microbot manipulator to show the effectiveness of the controller.

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.

Mirage is a camera pose estimation method that analytically solves pose parameters in linear time for multi-camera systems. It utilizes a reference camera pose to calculate the pose by minimizing the 2D projection error between reference and actual pixel coordinates. Previously, Mirage has been successfully applied to trajectory tracking (visual servoing) problem. In this study, a comprehensive evaluation of Mirage is performed by particularly focusing on the area of camera pose estimation. Experiments have been performed using simulated and real data on noisy and noise-free environments. The results are compared with the state-of-the-art techniques. Mirage outperforms other methods by generating fast and accurate results in all tested environments.

Haptic devices have proven effective in stimulating proprioceptive sensing in post-stroke patients. In this work, pre-existing devices were used together in a remote environment for the teleassessment of impaired hands. A four-channel bilateral control system in the presence of large and variable time delay is proposed as a proof of concept. Time delay is managed with a novel communication disturbance observer (CDOB). The system also employed a scaling down compensation value (SDCV) for the CDOB. The proposed control system was tested successfully in bilateral haptic interaction, simulating a remote motor and functional evaluation of patients' hands, guaranteeing safe and stable interaction, even in the presence of large network delays.

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.

In this paper, a method for the indirect solution of the optimal control problem (OCP) in the presence of pure state variable inequality constraints (SVICs) and mixed state-control inequality constraints (SCIC), without a need for a close initial guess is presented. In the proposed method, using the finite difference approximation (FDA), the pure SVICs are converted to SCIC. Here, the distance of the constraint function to the feasibility bounds of the constraint is computed in every situation and the control signal is chosen appropriately to facilitate the constraint stays safe. In this method, prior knowledge of the numbers and sequences of activation times is not required. So, it can be simply implemented in continuous boundary value problem (BVP) solvers. The proposed method simply applies the SVICs and since the constraint is directly applied on the control signal, it improves the convergence. On the other hand, because of the convergence problem in the indirect solution of OCP, the simple homotopy continuation method (HCM) is used to overcome the initial guess problem by deploying a secondary OCP for which the initial guess can be zero. The proposed approach is applied on a few comprehensive problems in the presence of different constraints. Simulations are compared with the direct solution of the OCP to confirm the accuracy and with the penalty function method and the sequential constraint-free OCP to confirm the convergence. The results indicate that the FDA method for handling the constraints along with the HCM is easy to apply with acceptable accuracy and convergence, even for highly nonlinear problems in robotic systems such as the constrained time optimal control of a two-link manipulator (TLM) and a three-link common industrial robot.

We present a fast object recognition system coding shape by viewpoint invariant geometric relations and appearance information. In our advanced industrial work-cell, the system can observe the work space of the robot by three pairs of Kinect and stereo cameras allowing for reliable and complete object information. From these sensors, we derive global viewpoint invariant shape features and robust color features making use of color normalization techniques.

We show that in such a set-up, our system can achieve high performance already with a very low number of training samples, which is crucial for user acceptance and that the use of multiple views is crucial for performance. This indicates that our approach can be used in controlled but realistic industrial contexts that require—besides high reliability—fast processing and an intuitive and easy use at the end-user side.

This paper proposes a new approach for slip prediction of walking biped robots. The slip prediction is a measurement-based and friction behavior-inspired approach. A measurement-based online algorithm is designed to estimate the Coulomb friction which is regarded as a slip threshold. To predict the slip, a safety margin is introduced in the negative vicinity of the estimated Coulomb friction. The estimation algorithm concludes that if the applied force is outside the safety margin, then the foot tends to slip. The proposed approach depends on the available type of measurements. Three options of measurements are discussed. Among them, the foot acceleration and ankle force measurements scenario is validated by experiments on the humanoid SURALP (Sabanci University Robotics Research Laboratory Platform). The results demonstrate the effectiveness of the proposed approach for slip prediction and detection.

Singular configurations of parallel manipulators (PMs) are special poses in which the manipulators cannot maintain their inherent infinite rigidity. These configurations are very important because they prevent the manipulator from being controlled properly, or the manipulator could be damaged. A geometric approach is introduced to identify singular conditions of planar parallel manipulators (PPMs) in this paper. The approach is based on screw theory, Grassmann–Cayley Algebra (GCA), and the static Jacobian matrix. The static Jacobian can be obtained more easily than the kinematic ones in PPMs. The Jacobian is expressed and analyzed by the join and meet operations of GCA. The singular configurations can be divided into three classes. This approach is applied to ten types of common PPMs consisting of three identical legs with one actuated joint and two passive joints.

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.

In this paper, we propose an enhanced Monte Carlo localization (EMCL) algorithm for mobile robots, which deals with the premature convergence problem in global localization as well as the estimation error existing in pose tracking. By incorporating a mechanism for preventing premature convergence (MPPC), which uses a “reference relative vector” to modify the weight of each sample, exploration of a highly symmetrical environment can be improved. As a consequence, the proposed method has the ability to converge particles toward the global optimum, resulting in successful global localization. Furthermore, by applying the unscented Kalman Filter (UKF) to the prediction state and the previous state of particles in Monte Carlo Localization (MCL), an EMCL can be established for pose tracking, where the prediction state is modified by the Kalman gain derived from the modified prior error covariance. Hence, a better approximation that reduces the discrepancy between the state of the robot and the estimation can be obtained. Simulations and practical experiments confirmed that the proposed approach can improve the localization performance in both global localization and pose tracking.

This paper proposes a leader following formation tracking controller for multiple underactuated underwater vehicles (UUVs) which move in three dimensional space. In order to avoid the derivative of the virtual control signals, a control method based on filter backstepping is proposed. The method can significantly simplify the design process of the backstepping controller through the use of a filter rather than the analytic derivation directly to the virtual control variable. Furthermore, the influence of measurement noise is obviously weakened. The stability of the formation system of multiple UUVs has been proved based on Lyapunov stability theory. Simulation results illustrate that the designed controller can track a three-dimensional formation trajectory accurately.

A new motion-free iterative closest point (ICP) algorithm is proposed for building a two-dimensional (2D) map for mobile robot navigation. A laser range finder (LRF) sensor is installed on a mobile robot to scan and measure the depth data of the environment to form a 2D map during mobile robot navigation. Because the scanning and navigation motions are performed independently, the scanned data contain distortions from the motions of the mobile robot. To compensate for the distortions, the proposed motion-free ICP algorithm estimates the effects of the dynamic motions of the robot on the scanning process. That is, the motion-free algorithm compensates for the distance measurement errors related to the dynamic changes in the mobile robot's velocity. Experiments were performed with actual velocity changes of a mobile robot to demonstrate and verify the effective performance of the proposed algorithm.

In order to potentially realize the advantages of planar parallel manipulators to be used for hybrid machine tools, the inherently abundant singularities which diminish the usable workspace must be eliminated. Proper structure synthesis and dimensional synthesis can provide a good solution. So, a non-conventional architecture of a three-PPR planar parallel manipulator is proposed in this paper for a hybrid machine tool. The proposed architecture permits a large dexterous workspace with unlimited orientation capability and no singularities. It also provides partially decoupled motion which permits independent actuators control. The kinematic, singularity, orientation capability and workspace analyses of the proposed manipulator are studied to verify those advantages. Based on a non-dimensional design parameter space, the highly important indices for this application namely the workspace index (WI), the motion/force transmission index, the kinematic and dynamic dexterity indices and the stiffness index are selected to be maximized yielding proper dimensions of the design parameters. Those performance indices are proven to be uniform over all the workspace achieving highly important characteristics of uniform accuracy, acceleration characteristics, rigidity and force transmissibility. Performance evaluation is finally presented to verify the high performance of the proposed non-singular planar parallel manipulator with high orientation capability.

In this paper, we study the problem of adaptive position tracking for a multi-link robot driven by two opposing pneumatic muscle groups with additive disturbances. In contrast to widely used sliding mode control methods, the proposed controller is continuous and able to prevent chattering. All physical parameters of the robot and the pneumatic muscles, including pneumatic muscle coefficients, link lengths and moments of inertia are unknown and can be time-varying and the unknown additive disturbances can be discontinuous. Under these conditions, we prove that closed-loop trajectories of all of the joint positions can track any C1 joint reference signal. The joint errors will be within a prescribed error bound in a finite time. The adaptive controller only uses the reference signal, not its derivative. The continuous adaptive gain is one-dimensional. Simulations including a two-link robot arm with friction and realistic muscle models are presented to demonstrate the robustness of the adaptive control under severe changes of the system parameters. In all simulations, the joint positions can track C1 trajectories and all errors are within the prescribed error bound in the same time frame, even though the muscle parameters are vastly different.

Redundancy in motion, and synergy in neuromuscular coordination provides significant versatility to the human fingers while performing coordinated grasping and manipulation tasks in several ways. This paper explores how humans may resolve the redundancy in their thumb, index and middle fingers when these digits flex to cooperatively translate a small object toward the palm. It is observed that humans actively employ a secondary subtask of maximizing instantaneous manipulability that helps determine all intermediate finger configurations when performing the primary subtask of following a tip trajectory. This behavior is accurately captured by an inverse kinematic model based on a redundancy parameter. The joint angles get determined unambiguously though the redundancy parameter is shown to depend on the instantaneous finger configurations and also, to attain negative values. Further, this parameter is noted to vary significantly across subjects performing the same kinematic task. The findings, that are based on the experimental finger motion data garnered from 12 subjects, are reckoned to be of significant importance, especially in reference to the challenges in design and control of finger exoskeletons for cooperative manipulation.

We propose a motor-driven capsule robot based on a sliding clamper (MCRSC), a device to explore the partially collapsed and winding intestinal tract. The MCRSC is powered by wireless power transmission based on near-field inductive coupling. It comprises a novel locomotion unit, a camera, and a three-dimensional receiving coil, all installed at both ends of the locomotion unit. The novel locomotion unit comprises a linear motion mechanism and a sliding clamper. The former adopts a pair of lead-screw and nut to obtain linear motion, whereas the latter anchors the MCRSC to a specific point of the intestinal tract by expanding its arc-shaped legs. The MCRSC is capable of two-way locomotion, which is activated by alternately executing linear motion and anchoring action. Ex vivo experiments have shown that the MCRSC is able to inspect the colon within a time frame of standard colonoscopy.

We propose a novel stereo visual IMU-assisted (Inertial Measurement Unit) technique that extends to large inter-frame motion the use of KLT tracker (Kanade–Lucas–Tomasi). The constrained and coherent inter-frame motion acquired from the IMU is applied to detected features through homogenous transform using 3D geometry and stereoscopy properties. This predicts efficiently the projection of the optical flow in subsequent images. Accurate adaptive tracking windows limit tracking areas resulting in a minimum of lost features and also prevent tracking of dynamic objects. This new feature tracking approach is adopted as part of a fast and robust visual odometry algorithm based on double dogleg trust region method. Comparisons with gyro-aided KLT and variants approaches show that our technique is able to maintain minimum loss of features and low computational cost even on image sequences presenting important scale change. Visual odometry solution based on this IMU-assisted KLT gives more accurate result than INS/GPS solution for trajectory generation in certain context.

The study of inertial forces effects at high speeds in flexible parallel manipulators, which generate undesired deviations, is a challenging task due to the coupled and complicated equations of motion. A dynamic model of the Revolute Prismatic Revolute (RPR) planar manipulators (specifically 3-RPR, 2-RPR and 1-RPR) with flexible intermediate links is developed based on the assumed mode method. The flexible intermediate links are modeled as Euler-Bernoulli beams with fixed-free boundary conditions. Using the Lagrange multipliers, a generalized set of differential algebraic equations (DAEs) of motion is developed. In the simulations, the rigid body motion of the end-effector is constrained by some moving constraint equations while the vibrations of the flexible intermediate links cause deviations from the desired trajectory. From this analysis, the dynamic performance of the manipulators when tracking a desired trajectory is evaluated. A comparison of the results indicates that in some cases, adding each extra RPR chain in the n-RPR planar manipulators with flexible intermediate links reduces the stiffness and accuracy due to the inertial forces of the flexible links, which is opposite to what would be expected. The study provides insights to the design, control and suitable selection of the flexible manipulators.