This paper presents the kinematics of a planar multibody vehicle which is aimed at the exploration, data collection, non-destructive testing and general autonomous navigation and operations in confined environments such as pipelines. The robot is made of several identical modules hinged by passive revolute joints. Every module is actuated with four active revolute joints and can be regarded as a parallel mechanism on a mobile platform. The proposed kinematics allows to overcome the nonholonomic kinematic constraint, which characterizes typical wheeled robots, resulting into a higher number of degrees of freedom and therefore augmented actuation inputs. Singularities in the kinematics of the modules are analytically identified. We present the dimensional synthesis of the length of the arms obtained as the solution of an optimization problem with respect to a suitable dexterity index. Simulation results illustrate a kinematic control path following inside pipes. Critical scenarios such as 135° elbows and concentric restriction are explored. Path following shows the kinematic capability of deployment of the robot for autonomous operations in pipelines, with feedback implemented by on-board sensors.

The demand for motor rehabilitation is growing apace with the graying of the population. The utilization of robotic devices in sensorimotor rehabilitation therapy has received increased attention during the last decade. Despite the growing interest in using robotic devices for rehabilitation of sensorimotor function, their widespread use remains somewhat limited by a number of factors, including the assessment of the true cost-to-benefit ratio relative to other types of rehabilitation approaches and parameters that would optimize their long-term efficacy. Understanding human sensorimotor control and brain plasticity can provide insight into the design of robot hardware and controllers with the appropriate reference or desired output. On the other hand, the control of the physical interaction of the therapeutic device with the subject to effectively accelerate recovery is of paramount importance. This special issue focuses on the current state of knowledge about sensorimotor control and brain plasticity, models of sensorimotor functional recovery, and use of intelligent robot controllers to provide robotic-assisted therapy for motor rehabilitation.

Zero moment point (ZMP) is the most popular concept that is applied to stabilize the gait motion of a biped robot. This paper utilizes ZMP with the augmented-reality (AR) method to improve the stability of gait motion of a biped robot. The 3ds Max computer software package is used to build a virtual robot. Under an achieved joint angle data of solid robot to produce an animation of the robot's trajectory, the joint angle data are transmitted to the virtual robot to analyze the offset of the trunk. Furthermore, this investigation adopts AR to allow the user to make direct comparisons between the solid and virtual robot before and after the gait motion is corrected. The animated trajectories of the virtual robot are compared and the relevant data provide feedback to the solid robot to adjust the joint angle and further correct its posture. The experimental results reveal that the proposed scheme can improve gait motion, even when the biped robot is affected by an unexpected loading disturbance. As well as improving the stability of gait motion of a biped robot, the results of this study can also be used to teach the application of the proposed method in a robotics class.

This paper presents a cable-driven dexterous manipulator with a large, open lumen. One specific application for the manipulator is the treatment of the degeneration of bone tissue (osteolysis) during a less-invasive hip revision surgery. Rigid tools used in traditional approaches limit the surgeons' ability to comprehensively treat the osteolysis due to the complex geometries of the lesion. The surgical scenario, testing, kinematic modeling, and image-based inverse kinematics are described. Testing shows 94% coverage of a lesion wall; the kinematic model describes manipulator notch positions within 0.15 mm, while the image-based inverse kinematics has 0.36 mm error. This manipulator is potentially useful in treating osteolytic lesions through (1) effective lesion exploration compared to conventional techniques, and (2) rapidly performing inverse kinematics from visual feedback.

In November 2012, the eleventh Workshop on Distributed Autonomous Robotic Systems (DARS 2012) was held in Baltimore, Maryland on the campus of Johns Hopkins University. Previous DARS workshops were held in 1992, 1994, and 1996 in Riken, Wako, Japan; Karlsruhe, Germany (1998); Knoxville, Tennessee, USA (2000); Fukuoka, Japan (2002); Toulouse, France (2004); Minneapolis, Minnesota, USA (2006); Tsukuba, Ibaraki, Japan (2008); and Lausanne, Switzerland (2010).

A new theory in contact pressure distribution and friction limit surfaces for modeling of hemicylindrical soft fingertips is introduced, to define the relationship between friction force and the moment with respect to the normal axis of contact. A general pressure-distribution function is proposed to capture material properties and contact geometry with various pressure profiles, and the coefficient of pressure distribution over the rectangular contact area is found between π and π/2. Combining the results of the contact mechanics model with the contact pressure distribution, the normalized friction limit surface can be derived for anthropomorphic soft fingers. The numerical friction limit surface of hemicylindrical soft-finger contact can be approximated by an ellipse, with the major and minor axes as the maximum friction force and the maximum moment with respect to the normal axis of contact, respectively. The results show that the friction limit surfaces are improved (13%–17%), if hemicylindrical fingertips are used rather than hemispherical fingertips at the same radius of fingertip, shape factor of the pressure profile, and applied load. Furthermore, the results of the contact mechanics model and the pressure distribution for soft fingers facilitate the construction of numerical friction limit surfaces, enabling to analyze and simulate the contact behaviors of grasping and manipulation in humanoid robots, prosthetic hands, and robotic hands.

In this paper, human viscosity perception in haptic teleoperation systems is thoroughly analyzed. An accurate perception of viscoelastic environmental properties such as viscosity is a critical ability in several contexts, such as telesurgery, telerehabilitation, telemedicine, and soft-tissue interaction. We study and compare the ability to perceive viscosity from the standpoint of detection and discrimination using several relevant control methods for the teleoperator. The perception-based method, which was proposed by the authors to enhance the operator's kinesthetic perception, is compared with the conventional transparency-based control method for the teleoperation system. The fidelity-based method, which is a primary method among perception-centered control schemes in teleoperation, is also studied. We also examine the necessity and impact of the remote-site force information for each of the methods. The comparison is based on a series of psychophysical experiments measuring absolute threshold and just noticeable difference for all conditions. The results clearly show that the perception-based method enhances both detection and discrimination abilities compare with other control methods. The results further show that the fidelity-based method confers a better discrimination ability than the transparency-based method, although this is not true with respect to detection ability. In addition, we show that force information improves viscosity detection for all control methods, as predicted from previous theoretical analysis, but improves the discrimination threshold only for the perception-based method.

This paper proposes a robot navigation scheme using wireless visual sensors deployed in an environment. Different from the conventional autonomous robot approaches, the scheme intends to relieve massive on-board information processing required by a robot to its environment so that a robot or a vehicle with less intelligence can exhibit sophisticated mobility. A three-state snake mechanism is developed for coordinating a series of sensors to form a reference path. Wireless visual sensors communicate internal forces with each other along the reference snake for dynamic adjustment, react to repulsive forces from obstacles, and activate a state change in the snake body from a flexible state to a rigid or even to a broken state due to kinematic or environmental constraints. A control snake is further proposed as a tracker of the reference path, taking into account the robot's non-holonomic constraint and limited steering power. A predictive control algorithm is developed to have an optimal velocity profile under robot dynamic constraints for the snake tracking. They together form a unified solution for robot navigation by distributed sensors to deal with the kinematic and dynamic constraints of a robot and to react to dynamic changes in advance. Simulations and experiments demonstrate the capability of a wireless sensor network to carry out low-level control activities for a vehicle.

In this paper, a new flexure-based micropositioning stage (FMPS) is proposed to achieve decoupled XY translational motions and large travel ranges. The stage consists of four independent kinematic chains, each comprising two flexure-beam prismatic joints. The mechanism with such a special topological structure enables the motions of the platform strictly along XY axes and minimizes the parasitic rotation in theta axis. The kinematics and dynamics analysis of the mechanism are conducted to evaluate the performance of the mechanism in terms of travel range, parasitic motions, linearity, as well as natural frequency. According to the developed models, a parameter optimization of the mechanism is performed under the condition of the maximum travel range. The finite element simulation is carried out to examine the mechanical performance and the theoretical models. The experimental results show that the proposed FMPS possesses a workspace of 600 × 600 μm2, a relative coupling error of 0.6%, and the natural frequencies of 209.7 Hz and 212.4 Hz for the first two modes.

An autonomous robot must obtain information about its surroundings to accomplish multiple tasks that are greatly improved when this information is efficiently incorporated into a map. Some examples are navigation, manipulation, localization, etc. This mapping problem has been an important research area in mobile robotics during last decades. It does not have a unique solution and can be divided into multiple sub-problems. Two different aspects of the mobile robot mapping problem are addressed in this work. First, we have developed a Differential Evolution-based scan matching algorithm that operates with high accuracy in three-dimensional environments. The map obtained by an autonomous robot must be consistent after registration. It is basic to detect when the robot is navigating around a previously visited place in order to minimize the accumulated error. This phase, which is called loop detection, is the second aspect studied here. We have developed an algorithm that extracts the most important features from two different three-dimensional laser scans in order to obtain a loop indicator that is used to detect when the robot is visiting a known place. This approach allows the introduction of very different characteristics in the descriptor. First, the surface features include the geometric forms of the scan (lines, planes, and spheres). Second, the numerical features are values that describe several numerical properties of the measurements: volume, average range, curvature, etc. Both algorithms have been tested with real data to demonstrate that these are efficient tools to be used in mapping tasks.

This paper presents a redundant 4-revolute (4R) spherical wrist mechanism for a shoulder exoskeleton, which overcomes several major issues with the 3R mechanisms used in the past. An analysis of the 3R mechanism is done to highlight the limitations in its range of motion and problems caused by operating near singular configurations. To ensure that the redundancy in the 4R mechanism is efficiently utilized, genetic algorithm is used to optimize the mechanism design and identify the optimal operating configurations of the mechanism. The capability to reach the entire shoulder workspace is guaranteed and the joint velocities are minimized by considering the joint displacements required to move the end-effector throughout the workspace and the condition number of joint configurations for reaching 89 positions in the workspace. Analysis of the 4R mechanism obtained from the optimization process indicates that it can move throughout the entire shoulder workspace with feasibly low joint velocities.

In the human body there are many joints whose functions are very similar to revolute joints. To avoid the complexity of these joints, they are usually substituted by revolute joints in many humanoid robots. Revolute joints have purely rotational motion along their fixed axis, while real joints in the human body have Instantaneous Rotational Axis (IRA) due to their configuration. Substitution of this kind of human joints with revolute (hinge) joints in robots changes the kinematics of joints. Knowing the exact characteristics of the moving axis of rotation in human joints is a prerequisite for the kinematic study of a joint. Here the main geometrical difference between these kinds of joints in humans and their simplified (hinge-like) models in robots is described. Then, as a case study, the mechanism of the three joints of the index finger are compared with their hinge-like model using a multi-body code to understand when revolute joints can be substituted for anthropometric joints in hand exoskeletons and robotic hands. Furthermore, the position of IRA and its distance from the center of the condyle of the joint are presented. The concept and the results can be extended for other fingers and all similar joints, and can be used in humanoid robots, hand exoskeletons and robotic hands.

We present the synthesis and analysis of distributed ensemble control policies to enable a team of robots to control their distribution across a collection of tasks. We assume that individual robot controllers are modeled as a sequential composition of individual task controllers. A macroscopic description of the team dynamics is then used to synthesize ensemble feedback control strategies that maintain the desired distribution of robots across the tasks. We present a distributed implementation of the ensemble feedback strategy that can be implemented with minimal communication requirements. Different from existing strategies, the approach results in individual robot control policies that maintain the desired mean and the variance of the robot populations at each task. We present the stability properties of the ensemble feedback strategy, verify the feasibility of the distributed ensemble controller through high-fidelity simulations, and examine the robustness of the strategy to sensing and/or actuation failures. Specifically, we consider the case when robots are subject to estimation and navigation errors resulting from lossy inter-agent wireless communication links and localization errors.

Mobile Ad hoc Networks have attracted much attention in the last years, since they allow the coordination and cooperation between agents belonging to a multi-robot system. However, initially deploying autonomously a wireless sensor robot network in a real environment has not taken the proper attention. Moreover, maintaining the connectivity between agents in real and complex environments is an arduous task since the strength of the connection between two nodes (i.e., robots) can change rapidly in time or even disappear. This paper compares two autonomous and realistic marsupial strategies for initial deployment in unknown scenarios, in the context of swarm exploration: Random and Extended Spiral of Theodorus. These are based on a hierarchical approach, in which exploring agents, named scouts, are autonomously deployed through explicit cooperation with supporting agents, denoted as rangers. Experimental results with a team of heterogeneous robots are conducted using both real and virtual robots. Results show the effectiveness of the methods, using a performance metric based on dispersion. Conclusions drawn in this work pave the way for a whole series of possible new approaches.

In this paper, we revisit the 3-degrees of freedom (DOF) pure translational mechanism. The mathematical model and the design considerations are discussed. A detailed sensitivity and error analysis is carried out and the results are discussed in a new perspective. The feasibility of the practical 3-DOF pure translational mechanism is established with novel design considerations to take care of theoretical mobility and geometrical constraints. We describe and validate the theoretical observations with stage-wise prototype models and experiments. The experimental results concur that all is well with 3-UPU in contrast to what is presented in refs. [6, 9, 10].

In this study, we attempt to develop a biped dinosaur-like walking robot by focusing on its nervous system as well as its mechanism. We developed a robot ‘Dinobot’ on the basis of palaeontological knowledge on dinosaurs and extant animals. In addition, we employed typical biologically inspired walking gait generation and control methods derived from an extant vertebrate's nervous system. In particular, we utilized a central pattern generator (CPG), which is a locomotion rhythm generator in a vertebrate's spinal cord, to generate the robot's walking rhythm. Moreover, a reflex centre was placed below CPG and it produced joint torque of the legs in the swing and stance phases. Thus, we successfully achieved adaptive 3D dynamic walking generated by the interaction between the original mechanism of dinosaurs and the nervous system of extant animals. Our future goal is to find out a dinosaur's robust locomotive nervous system suitable for its mechanism.

This paper investigates the kinematics and the optimization of a generic robotic structure composed by N serial rotary joints and actuated with a mono-directional tendon system. In the first part of the paper, the specific case that brought us to develop this study is introduced; the main motivations and the scenario with its specific constraints and design choices have been described.

Since a complete and detailed analysis of an n-R serial structure with this kind of characteristics could not be found in the literature, the study of the kinematics and the parameter optimization of such a structure is treated as generally as possible, in order to make the procedure and the results applicable for any similar structure. Finally, in the last part, through the introduction of specific constraints and the definition of the parameters, the general analysis has been applied to the specific case of study: the preliminary study of a finger exoskeleton for an astronaut suit.

We present a control method for a simple limit-cycle bipedal walker that uses adaptive frequency oscillators (AFOs) to generate stable gaits. Existence of stable limit cycles is demonstrated with an inverted-pendulum model. This model predicts a proportional relationship between hip torque amplitude and stride frequency. The closed-loop walking control incorporates adaptive Fourier analysis to generate a uniform oscillator phase. Gait solutions (fixed points) are predicted via linearization of the walker model, and employed as initial conditions to generate exact solutions via simulation. Global stability is determined via a recursive algorithm that generates the approximate basin of attraction of a fixed point. We also present an initial study on the implementation of AFO-based control on a bipedal walker with realistic mass distribution and articulated knee joints.

A brain–computer interface (BCI) is a system for commanding a device by means of brain signals without having to move any muscle. One kind of BCI is based on Steady-State Visual Evoked Potentials (SSVEP), which are evoked visual cortex responses elicited by a twinkling light source. Stimuli can produce visual fatigue; however, it has been well established that high-frequency SSVEP (>30 Hz) does not. In this paper, a mobile robot is remotely navigated into an office environment by means of an asynchronous high-frequency SSVEP-based BCI along with the image of a video camera. This BCI uses only three electroencephalographic channels and a simple processing signal method. The robot velocity control and the avoidance obstacle algorithms are also herein described. Seven volunteers were able to drive the mobile robot towards two different places. They had to evade desks and shelves, pass through a doorway and navigate in a corridor. The system was designed so as to allow the subject to move about without restrictions, since he/she had full robot movement's control. It was concluded that the developed system allows for remote mobile robot navigation in real indoor environments using brain signals. The proposed system is easy to use and does not require any special training. The user's visual fatigue is reduced because high-frequency stimulation is employed and, furthermore, the user gazes at the stimulus only when a command must be sent to the robot.

A novel rigid-body control design methodology for 6-degree-of-freedom (dof) parallel kinematic mechanisms (PKMs) is proposed. The synchronous control of PKM joints is addressed through a novel formulation of contour and lag errors. Robust performance as a control specification is addressed. A convex combination controller design approach is applied to address the problem of simultaneously satisfying multiple closed-loop specifications. The applied dynamic modeling approach allows the design methodology to be extended to 6-dof spatial PKMs. The methodology is applied to the design of a 6-dof PKM-based meso-milling machine tool and simulations are conducted.