This paper presents a new configuration for ankle rehabilitation using a 9-DOF (degree of freedom) hybrid parallel robot. The robot contains nine linear actuators serially connecting two movable platforms and one stationary platform. The optimization is based on the singularity and dynamic analysis of the robot. The obtained data of the ankle motions from a series of experiments were applied to the model in order to investigate the motion of the end-effector and the force required for each actuator in a particular path. The end-effector tracking simulation results validated the proposed theoretical analysis of the required rehabilitation path of the foot.

This paper deals with the control of an active ankle foot orthosis (AAFO) for paretic patients. State of the art methods using an AAFO try to track a predefined trajectory of the ankle joint while guaranteeing the wearer’s safety in the presence of a large tracking error. Combining the wearer’s safety and tracking accuracy is generally difficult to achieve at the same time, hence a trade-off should be found. Proxy-based sliding mode control (PSMC) offers great performances in both position tracking and safety guarantee. However, its tracking performance is subject to the influences of parameter uncertainties and external disturbances that generally occur during walking. This paper introduces an adaptation interaction method to the basic PSMC with an online adaptation of the proportional, integral and derivative parameters. At the same time, a gait phase-based ankle reference generation algorithm was proposed to adjust the joint reference trajectory in real time. The experiments using the AAFO show better tracking results with respect to basic PSMC while guaranteeing the safety.

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.

In this paper, an application is presented of a cable-based parallel manipulator as measuring system for an experimental identification of human walking characteristics. Experimental results have been obtained by means of a new version of CaTraSys (Cassino Tracking System), which is a measuring system that has been designed and built at Laboratory of Robotics and Mechatronics (LARM) in Cassino, Italy. The new version of the CaTraSys system has been used to determine the trajectory of the human limb extremity during walking operation and furthermore the system is able to measure forces that are exerted by a limb. Experimental determination of articulation mobility is also presented with numerical and experimental results.

For reproducing the manipulation of Traditional Chinese Medicine (TCM) remedial massage and meanwhile guaranteeing safety, a 4-degree-of-freedom anthropomorphic robotic arm with integrated elastic joints is developed, and a passivity-based impedance control is used. Due to the series elasticity, integrated joints may minimize large forces that occur during accidental impacts, and, further, may offer more accurate and stable force control and a capacity for energy storage. Human expert's fingertip force curve in the process of massage therapy is acquired in vivo by a dedicated measurement device. Then three massage techniques, pressing, kneading, and plucking, are implemented by the soft arm, respectively, on torso model in vitro and on human body in vivo. Experimental results show that the developed robotic arm can effectively replicate the TCM remedial massage techniques.

Real-time localization is an important mission for self-driving cars and it is difficult to achieve precise pose information in dynamic environments. In this paper, a novel localization method is proposed to estimate the pose of self-driving cars using a 3D-LiDAR sensor. First, the multi-frame curb features and laser intensity features are extracted. Meanwhile, based on the high-precision curb map generated offline, obstacles on road are detected using region segmentation methods and their features are removed. Furthermore, a map-matching method is proposed to match the features to the map, a robust iterative closest point algorithm is utilized to deal with curb features along with a probability search method dealing with intensity features. Finally, two separate Kalman filters are used to fuse the low-cost global positioning systems and map-matching results. Both offline and online experiments are carried out in dynamic environments and the results demonstrate the accuracy and robustness of the proposed method.

Cooperative transportation by human and robotic coworkers constitutes a challenging research field that could lead to promising technological achievements. Toward this direction, the present work demonstrates that, under a leader–follower architecture, where the human determines the object’s desired trajectory, complex cooperative object manipulation with minimal human effort may be achieved. More specifically, the robot estimates the object’s desired motion via a prescribed performance estimation law that drives the estimation error to an arbitrarily small residual set. Subsequently, the motion intention estimation is utilized in the object dynamics to determine the interaction force between the human and the object. Human effort reduction is then achieved via an impedance control scheme that employs the aforementioned estimations. The feedback relies exclusively on the robot’s force/torque, position as well as velocity measurements at its end effector, without incorporating any other information on the task. Moreover, an adaptive control scheme is adopted to relax the need for exact knowledge of the object dynamics. Finally, an extension for multiple robotic coworkers is studied and verified via simulation, while extensive experimental results for the single robot case clarify the proposed method and corroborate its efficiency.

FastSLAM is a framework for simultaneous localization and mapping using a Rao-Blackwellized particle filter (RBPF). But, FastSLAM is known to degenerate over time due to the loss of particle diversity, mainly caused by the particle depletion problem in resampling phase. In this work, improved particle filter using geometric relation between particles is proposed to restrain particle depletion and to reduce estimation errors and error variances. It uses a KD tree (k-dimensional tree) to derive geometric relation among particles and filters particles with importance weight conditions for resampling. Compared to the original particle filter used in FastSLAM, this technique showed less estimation error with lower error standard deviation in computer simulations.

This paper presents a robust adaptive output feedback tracking controller for the flexible-joint robot manipulators to deal with the unknown upper bounds of parameter uncertainties and external disturbances. With applying the singular perturbation theory and integral manifold concept, the complex nonlinear coupled system of the flexible-joint robot manipulators is divided into a slow subsystem and a fast subsystem. A robust adaptive control scheme based on an improved linear parameterization expression is designed for the slow subsystem, and a saturation function is applied in the robust control term to make the torque output smooth. In the meantime, different from the previous approaches, the second-order derivative term of elastic torque is avoided by using the proposed computed torque method, which simplifies the implementation of the fast control law. Moreover, to carry out the whole control system with only position measurements, an approximate differential filter is involved to generate pseudo velocity signals for links and joint motors. In addition, an explicit but strict stability proof of the control system based on the theory of singularly perturbed systems is presented. Finally, simulation results verify the superior dynamic performance of the proposed controller.

This paper deals with a comparative study of two planar two degrees of freedom parallel mechanisms: one with 2-RRR and the other with 3-RRR structures. For a fair comparison, both 3-RRR and 2-RRR mechanisms are symmetrical. The kinematics and Jacobian matrix of the two mechanisms are studied. Conditioning index, stiffness index and payload index are proposed to compare the condition, stiffness and payload performance of the two mechanisms. The results show that the 2-RRR and 3-RRR mechanisms have the similar condition performance, and the planar 3-RRR mechanism has better payload and stiffness performance than the 2-RRR one.

Minimum distance algorithms allow users of robot simulation programs to maneuver manipulation arms around and between workspace obstacles. Additionally, they can be used to generate configuration maps for path planning of the manipulator “point” through a more abstract configuration space. This paper summarizes an algorithm for determining minimum distances between two polyhedral elements. Examples of configuration space maps and Cartesian stepping techniques demonstrate algorithmic utility for robot path planning. A number of accelerating strategies which depend on a heirarchical spatial representation of manipulator and workspace elements maintain reasonable CPU times for the simulation user.

This paper considers a problem of tracking control design for different types of nonholonomic mobile manipulators. The mobile platform is in form of a unicycle. In the first step, an input–output decoupling controller is developed. The proposed selection of output functions is in more general form than the output functions previously introduced by others [Yamamoto and Yun]. It makes possible to move simultaneously, the mobile platform and the manipulator built on it. Regularity conditions that guarantee the existence of the input–output decoupling control law are presented. In the second step, trajectory and path tracking controllers are formulated and presented. Theoretical considerations are illustrated with simulations for the mobile manipulator consisting of a vertical, three degree of freeedom (DOF) pendulum (with holonomic or nonholonomic drives) mounted atop of a unicycle.

This paper proposes a prediction system and a command fusion to help the human operator in a teleoperation system of a mobile robot with time-varying delay and force feedback. The command fusion is used to join a remote controller and the delayed user's commands. Besides, a predictor is proposed since the future trajectory of the mobile robot is not known a priori being it decided online by the user. The command fusion and predictor are designed based on the time delay and the current context measured through the crash probability. Finally, the proposed scheme is tested from teleoperation experiments considering time-varying delay as well as force feedback.

The force distribution problem in multilegged vehicle is a constrained, optimization problem. The solution to the problem is the setpoints of the leg contact forces for a particular system task. In this paper, the efficient Compact QP method which takes into account both the linear and quadratic objective functions is adopted to resolve this constrained, optimization problem. Various objective functions such as minimum force, load balance, safety margin on friction constraints can be considered by the Compact QP method. This method can also be applied to smooth discontinuities in commanded forces by manipulating the homogeneous solution and including smoothing periods when the leg phase alternates between support and transfer. This smoothing scheme does not require force sensors. Multiple goals which consider several alternative objective functions can also be achieved by the Compact QP method.

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.

A disturbance rejection controller is proposed based on the general dynamic model of 3D biped robots. For the first time, with this proposed approach, not only the Zero Moment Point (ZMP) location remains unchanged in presence of disturbances but also the longitudinal and lateral ground reaction forces and the vertical twist moment remain unchanged. This way, slipping as well as tipping is prevented by the controller. The swing phase of the robot's walking gait is considered. An integral sliding mode architecture is chosen for the disturbance rejection. The support forces and moments of the stance foot are the control outputs. The acceleration of the arm/body joints are chosen as the inputs. During the disturbance rejection, the leg joints remain at their desired trajectory. Since the leg joint trajectories are unaffected, the robot is still able to complete its step as planned, even when bounded disturbances are experienced. For simulations, the general method is applied to an 18-degree of freedom biped humanoid robot. Simulations show that the controller successfully mitigates bounded disturbances and maintains all of the support reactions extremely close to their desired values. Consequently, the shift in the position of the ZMP is negligible, and the robot foot does not slip.

This paper studies crab gaits and turning gaits of a hexapod robot with a locked joint failure. Due to the reduced workspace of a failed leg, fault-tolerant gaits have limitations in their mobility. Based on the principles of fault-tolerant gait planning, periodic crab gaits and turning gaits are proposed in which a hexapod robot carries out tripod walking after a locked joint failure, having a reasonable stride length and stability margin.

Design of balancing control and the stability analysis of a biped during disturbed standing are investigated. A PD-based switching state feedback control is used to stabilize the biped at the upright position while satisfying the constraints between the feet and the ground. The concept of Lyapunov exponents is used for the stability analysis, and a stability region is determined. Furthermore, the stability region is compared and agrees well with the one from the previous work that predicts the feasible movement during which balance of human standing can be maintained. This agreement shows the potential of the concept of Lyapunov exponents to be used as a measure of balancing of human standing. The work contributes to bipedal balancing control, which is important in the development of bipedal robots.

Undulatory fin propulsion, inspired by the locomotion of aquatic species such as electric eels and cuttlefish, holds considerable potential for endowing underwater vehicles with enhanced propulsion and maneuvering abilities, to address the needs of a growing number of applications. However, there are still gaps in our understanding of the effect of the fin undulations' characteristics on the generated thrust, particularly within the context of developing propulsion control strategies for such robotic systems. Towards this end, we present the design and experimental evaluation of a robotic fin prototype, comprised of eight individually-actuated fin rays. An artificial central pattern generator (CPG) is used to produce the rays' undulatory motion pattern. Experiments are performed inside a water tank, with the robotic fin suspended from a carriage, whose motion is constrained via a linear guide. The results from a series of detailed parametric investigations reveal several important findings regarding the effect of the undulatory wave kinematics on the propulsion speed and efficiency. Based on these findings, two alternative strategies for propulsion control of the robotic fin are proposed. In the first one, the speed is varied through changes in the undulation amplitude, while the second one involves simultaneous adjustment of the undulation frequency and number of waves. These two strategies are evaluated via experiments demonstrating open-loop velocity control, as well as closed-loop position control of the prototype.

This study focuses on a door-opening mobile manipulator operating in four phases (reaching the door, grasping the door handle, turning the door handle, and pulling the door). We use force/torque feedback-based control, achieving compliance of the mobile base when it comes into contact with the handle. A method is proposed for estimating the unknown force-related constraints from manipulator joint position measurements. A robust adaptive control strategy is developed for tracking the planned trajectory to open the door. Finally, a mobile manipulator opens a real door with a locked latch and unknown force-related constraints, demonstrating the validity of the proposed approach.