In this study, the kinematics and dynamics of a single actuator wave (SAW)-like robot are explored. Comprising a helical spine and links, SAW has the potential for miniaturization. A kinematic model for SAW is firstly established, and the dynamic equation of motion is derived based on Kane’s method. For validation, the motion of SAW is simulated using both MATLAB and ADAMS, and the comparison of results demonstrates the effectiveness of the theoretical models. Then the inverse dynamic analysis is performed to reveal the power consumption. Finally, robot prototypes are developed and tested to confirm the robot velocity predicted by simulations.

The paper presents physical modeling, design, simulations, and experimentation on a novel Soft Underwater Artificial Skin (SUAS) used as tactile sensor. The SUAS functions as an electrostatic capacitive sensor, and it is composed of a hyperelastic membrane used as external cover and oil inside it used to compensate the marine pressure. Simulation has been performed studying and modeling the behavior of the external interface of the SUAS in contact with external concentrated loads in marine environment. Experiments on the external and internal components of the SUAS have been done using two different conductive layers in oil. A first prototype has been realized using a 3D printer. The results of the paper underline how the soft materials permit better adhesion of the conductive layer to the transducers of the SUAS obtaining higher capacitance. The results here presented confirmed the first hypotheses presented in a last work and opened new ways in the large-scale underwater tactile sensor design and development. The investigations are performed in collaboration with a national Italian project named MARIS, regarding the possible extension to the underwater field of the technologies developed within the European project ROBOSKIN.

Determining an appropriate grasp configuration for multi-finger grasping is difficult due to the complexity of robotic hands. The multi-finger grasp planning should consider not only geometry constraints of objects but also kinematics and dynamics of robotic hand. In this paper, a precision grasp-planning framework is presented for multi-finger hand to grasp unknown objects. First, the manipulation capabilities of the robotic hand are analyzed. The analysis results are further used as bases for the precision grasp planning. Second, the superquadric (SQ) fitting method is used for approximating unknown object models. Finally, a local–global optimization method is implemented to find appropriate grasp configurations for dexterous hand. The presented planning framework is validated in simulation experiments. Simulation results demonstrated that the presented grasp-planning framework enables the multi-finger hand to grasp unknown objects effectively.

Though significant efforts are made to develop mathematical models of the limit cycle walking (LCW), there is still a lack of a general and efficient framework to study the periodic solution and robustness of a complex model like human with knees, ankles and flat feet. In this study, a numerical framework of the LCW based on general multibody system dynamics is proposed, especially the impacts between the feet and the ground are modeled by Hunt–Crossley normal contact force and Coulomb friction force, and the modeling of the knee locking is presented as well. Moreover, event-based operating strategies are presented to deal with controls for the ground clearance and the knee locking. Importantly, a fast and efficient two-step algorithm is proposed to search for stable periodic gaits. Finally, maximum allowable disturbance is adopted as the index for stability analysis. All these features could be readily implemented in the framework. The presented solution is verified on a compass-like passive dynamic walking (PDW) walker with results in the literature. Based on this framework, a fairly complicated level-walking walkers with ankles and knees under control are analyzed and their periodic gaits are obtained, and surprisingly, double stable periodic gaits with, respectively, low speed and high speed are found.

Previous researches on analysis of stability of haptic simulation largely assume that the virtual environment is passive. But the virtual environment can become non-passive due to various reasons including discretization errors and interaction dynamics between virtual tools and objects. This paper provides an analysis of the stability and performance of the haptic simulation involving non-passive virtual environment. The dynamic interaction between the virtual tools and the objects is modeled using the two-port networks. The analysis is carried out using a velocity and force mapping matrix for six-DOF simulation. New stability condition resulting from the analysis is applied to an example simulation of a one-DOF virtual wall. Maximum stiffness satisfying the stability condition established in the previous literature, and the proposed condition is compared with the maximum stiffness experimentally determined with various time steps. The newly proposed stability condition manifests less standard deviation of errors than the widely applied absolute stability condition.

When using parallel manipulators as machine tools, their stiffness is an important factor in the quality of the produced products. This paper presents an overall approximate stiffness model for a heavy-load parallel manipulator, which considers the effects of actuator stiffness, joint clearance, joint contact deformation, and limb deformation. Based on the principle of virtual work and the introduced modified parameters, the proposed overall compliance matrix successfully takes four factors into a unified expression. To obtain the overall compliance matrix, the approximate stiffness models of the joint clearance, joint contact deformation, and limb deformation are given. In addition, by combining the statistical simulation including the random uncertainties and the proposed approximate stiffness models as the basis of the magnitudes for each random variable, an approach based on the expected trajectory and external load is also proposed for stiffness defect identification such that the estimation is more accurate and reliable. Finally, a numerical example of the 1PU+3UPS parallel manipulator and a discussion are presented to demonstrate the practicability of the proposed stiffness model and defect identification approach. After modifying the structure parameters of the defective components, the prototype experiences a significant stiffness improvement.

This paper presents visual and 3D structure inspection for steel structures and bridges using a developed climbing robot. The robot can move freely on a steel surface, carry sensors, collect data and then send to the ground station in real-time for monitoring as well as further processing. Steel surface image stitching and 3D map building are conducted to provide a current condition of the structure. Also, a computer vision-based method is implemented to detect surface defects on stitched images. The effectiveness of the climbing robot's inspection is tested in multiple circumstances to ensure strong steel adhesion and successful data collection. The detection method was also successfully evaluated on various test images, where steel cracks could be automatically identified, without the requirement of some heuristic reasoning.

It is well known that the sense of presence in a tele-robot system for both home-based tele-rehabilitation and rescue operations is enhanced by haptic feedback. Beyond several advantages, in the presence of communication delay haptic feedback can lead to an unstable teleoperation system. During the last decades, several control techniques have been proposed to ensure a good trade-off between transparency and stability in bilateral teleoperation systems under time delays. These proposed control approaches have been extensively tested with teleoperation systems based on identical master and slave robots having few degrees of freedom (DoF). However, a small number of DoFs cannot ensure both an effective restoration of the multi-joint coordination in tele-rehabilitation and an adequate dexterity during manipulation tasks in rescue scenario. Thus, a deep understanding of the applicability of such control techniques on a real bilateral teleoperation setup is needed. In this work, we investigated the behavior of the time-domain passivity approach (TDPA) applied on an asymmetrical teleoperator system composed by a 5-DoFs impedance designed upper-limb exoskeleton and a 4-DoFs admittance designed anthropomorphic robot. The conceived teleoperation architecture is based on a velocity–force (measured) architecture with position drift compensation and has been tested with a representative set of tasks under communication delay (80 ms round-trip). The results have shown that the TDPA is suitable for a multi-DoFs asymmetrical setup composed by two isomorphic haptic interfaces characterized by different mechanical features. The stability of the teleoperator has been proved during several (1) high-force contacts against stiff wall that involve more Cartesian axes simultaneously, (2) continuous contacts with a stiff edge tests, (3) heavy-load handling tests while following a predefined path and (4) high-force contacts against stiff wall while handling a load. The found results demonstrated that the TDPA could be used in several teleoperation scenarios like home-based tele-rehabilitation and rescue operations.

Consider the practically relevant situation in which a robotic system is assigned a task to be executed in an environment that contains moving obstacles. Generating collision-free motions that allow the robot to execute the task while complying with its control input limitations is a challenging problem, whose solution must be sought in the robot state space extended with time. We describe a general planning framework which can be tailored to robots described by either kinematic or dynamic models. The main component is a control-based scheme for producing configuration space subtrajectories along which the task constraint is continuously satisfied. The geometric motion and time history along each subtrajectory are generated separately in order to guarantee feasibility of the latter and at the same time make the scheme intrinsically more flexible. A randomized algorithm then explores the search space by repeatedly invoking the motion generation scheme and checking the produced subtrajectories for collisions. The proposed framework is shown to provide a probabilistically complete planner both in the kinematic and the dynamic case. Modified versions of the planners based on the exploration–exploitation approach are also devised to improve search efficiency or optimize a performance criterion along the solution. We present results in various scenarios involving non-holonomic mobile robots and fixed-based manipulators to show the performance of the planner.

For a real-time robotic prosthetic control, gait event detection plays an important role. In this paper, one novel sensor was proposed to realize gait event detection. The sensor includes one strain gauge bridge, which can reflect the entire deformation of carbon-fiber footplate on a robotic prosthesis. Three unilateral transtibial amputees participated in the experiments. Experimental results show that using the proposed sensor method, gait event detection (stance phase and swing phase) accuracy is approximately 100%. Based on the detected gait events, three locomotion modes (sit, stand, and walk) and the corresponding transition modes could be determined. Difference between different gait event detection systems was further conducted.

Position-tracking problems in the structures of rigid formations of nonholonomic mobile robots, such as fixed-wing unmanned aerial vehicle (UAVs), must reconcile tracking precision and flight stability, which usually exclude each other due to nonholonomic motion constraints. Therefore, a position-tracking control that is based on distance and position displacement, defined as inputs of control loops, requires the application of dead zones around target positions, which are the points of instability. For this reason, the control becomes sensitive to any external disturbance causing oscillations of control signals and so it becomes difficult to maintain a zero value of position displacement over a long time horizon. Thus, we propose an approach based on the adaptive mechanism of an asymmetrical local artificial potential field, which is defined by a local frame of reference whose origin is located in the tracked position of a UAV in the formation frame. It couples controls of both airspeed and heading angle into a nonlinear potential function of relative position and orientation with respect to the tracked position and adapts it according to heading rate of the leader. The function splits the area around the tracked position longitudinally into two zones of acceleration and deceleration; therefore, velocity vectors are longer (higher airspeed) only when a UAV is behind the tracked position and shorter (lower airspeed) when it is ahead. The area is laterally symmetrical, and orientations of velocity vectors align asymptotically to the longitudinal direction accordingly with the decrease in the lateral error. Finally, velocity vectors are rotated proportionally to the heading rate of the leader, which improves the tracking precision during turns. If we assumed that a UAV’s tracked position is in motion, it could easily be proven that the position control based on the adaptive asymmetrical potential function becomes asymptotically stable in the tracked position. Numerical simulation verifies this thesis and presents more precise and stable position tracking due to the adaptation mechanism.

In this work a simple method to solve the kinematics of the 5-R$\underbar{P}$UR parallel manipulator is introduced. Dealing with the displacement analysis, the kinematic constraint equations required to address the forward–inverse displacement analysis are established according to linear combinations of two vectors attached to the moving platform. Then, besides the solution of the inverse displacement analysis two strategies are proposed in order to solve the forward position analysis. Finally, the input–output equations of velocity and acceleration are systematically obtained by resorting to reciprocal-screw theory. Numerical examples are provided with the purpose to illustrate the proposed method. Furthermore, the numerical results obtained by means of screw theory are confirmed with the aid of commercially available software.

This paper proposes a dynamic window with virtual goal (DW-VG) method for local collision avoidance in dynamic environments. Firstly, the debounce filter and polynomial curve-fitting algorithm are combined to predict the trajectory of the obstacles with timestamps. Based on the motion prediction of the obstacles, the virtual goal is proposed to replace the real goal, so that the robot can escape from the concave trap and avoid the dynamic obstacles. According to the timestamps and virtual goal, the optimal linear and angular velocities are selected from the dynamic window, which drive the robot toward its real goal. The simulation and experimental results show that the DW-VG method can not only escape the local minima and avoid dynamic obstacles but also is applicable to the dense environment. Furthermore, the simulation results also verify that the DW-VG method drives the robot to reach its goal faster and safer than other reactive obstacle avoidance methods.

With the increasing demands for versatile robotic platforms capable of performing a variety of tasks in diverse and uncertain environments, the needs for adaptable robotic structures have been on the rise. These requirements have led to the development of modular reconfigurable robotic systems that are composed of a numerous self-sufficient modules. Each module is capable of establishing rigid connections between multiple modules to form new structures that enable new functionalities. This allows the system to adapt to unknown tasks and environments. In such structures, coupling between modules is of crucial importance to the overall functionality of the system. Over the last two decades, researchers in the field of modular reconfigurable robotics have developed novel coupling mechanisms intended to establish rigid and robust connections, while enhancing system autonomy and reconfigurability. In this paper, we review research contributions related to robotic coupling mechanism designs, with the aim of outlining current progress and identifying key challenges and opportunities that lay ahead. By presenting notable design approaches to coupling mechanisms and the most relevant efforts at addressing the challenges of sensorization, misalignment tolerance, and autonomous reconfiguration, we hope to provide a useful starting point for further research into the field of modular reconfigurable robotics and other applications of robotic coupling.

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.