There is increasing interest in using rehabilitation robots to assist post-stroke patients during rehabilitation therapy. The motion control of the robot plays an important role in the process of functional recovery training. Due to the change of the arm impedance of the post-stroke patient in the passive recovery training, the conventional motion control based on a proportional-integral (PI) controller is difficult to produce smooth movement of the robot to track the designed trajectory set by the rehabilitation therapist. In this paper, we model the dynamics of post-stroke patient arm as an impedance model, and propose an adaptive control scheme, which consists of an adaptive PI control algorithm and an adaptive damping control algorithm, to control the rehabilitation robot moving along predefined trajectories stably and smoothly. An equivalent two-port circuit of the rehabilitation robot and human arm is built, and the passivity theory of circuits is used to analyze the stability and smoothness performance of the robot. A slide Least Mean Square with adaptive window (SLMS-AW) method is presented for on-line estimation of the parameters of the arm impedance model, which is used for adjusting the gains of the PI-damping controller. In this paper, the Barrett WAM Arm manipulator is used as the main hardware platform for the functional recovery training of the post-stroke patient. Passive recovery training has been implemented on the WAM Arm, and the experimental results demonstrate the effectiveness and potential of the proposed adaptive control strategies.

This paper studies the modeling and analysis of a system with two cooperative manipulators working together on a common task. The task is defined as the transportation of an object in space. The cooperative system is the dual-arm of the humanoid robot Nao, where the serial architecture of each arm has 5 degrees of freedom. The kinematics representing the closed chain system is studied. The mobility of the closed-loop system is analyzed and the nature of the possible motions explored. The stiffness of some motors can be reduced until they behave as passive joints. Certain joints are then chosen as actuated (independent) and the others as passive (dependent). The serial and parallel singular configurations of the system are considered. From the kinematic analysis, admissible and inadmissible minimum actuation schemes are analyzed. Furthermore the dynamic performance of the schemes is compared to find the optimum minimum actuation scheme.

In SLAM (simultaneous localization and mapping), the topological paradigm provides a more natural and compact solution that scales better with the size of the environment. Computer vision has always been regarded as the ideal sensor technology for topological feature extraction and description and several methods have been proposed in the literature, but they are either time-consuming, require plenty of different sensors, or are very sensitive to perceptual aliasing, all of which limit their application scope.

This paper presents a fast-to-compute collection of features extracted from monocular images, and an adaptive matching procedure for location identification in structured indoor environments inspired by the natural language processing field. Although only dominant vertical lines, color histograms, and a reduced number of keypoints are employed in this paper, the matching framework introduced allows for the incorporation of almost any other type of feature. The results of the experiments carried out in a home and an office environment suggest that the proposed method could be used for real-time topological scene recognition even if the environment changes moderately over time. Due to the combination of complementary features, high precision can be achieved within reasonable computation time by using weaker but faster descriptors.

This paper presents analysis of the dynamics and vibration of an orientation motion platform utilizing a sphere actuated by omnidirectional wheels. The purpose of the analysis is to serve as a design tool for the construction of a six-degree-of-freedom motion platform with unlimited rotational motion. The equations of motion are presented taking flexibility of the system into account. The behaviour of the system is illustrated by sample configurations with a range of omnidirectional wheel types and geometries. Vibration analysis follows, and sensitivity to various parameters is investigated. It is determined that the geometry of omnidirectional wheels has a significant effect on the behaviour of the system.

Path planning is one of the most important fields in robotics. Only a limited number of articles have proposed a practical way to solve the path-planning problem with moving obstacles. In this paper, a fuzzy path-planning method with two strategies is proposed to navigate a robot among unknown moving obstacles in complex environments. The static form of the environment is assumed to be known, but there is no prior knowledge about the dynamic obstacles. In this situation, an online and real-time approach is essential for avoiding collision. Also, the approach should be efficient in natural complex environments such as blood vessels. To examine the efficiency of the proposed algorithm, a drug delivery nanorobot moving in a complex environment (blood vessels) is supposed. The Monte Carlo simulation with random numbers is used to demonstrate the efficiency of the proposed approach, where the dynamic obstacles are assumed to appear in exponentially distributed random time intervals.

In this paper, two methods are proposed and implemented for collision detection between the robot and a human based on fuzzy identification and time series modelling. Both methods include a collision detection system for each joint of the robot that is trained to approximate the external torque. In addition, the proposed methods are able to detect the occurrence of a collision, the link that collided and to some extent the magnitude of the collision without using the explicit model of the robot. Since the speed of the detection is of critical importance for mitigating the danger, attention is paid to recognise a collision as soon as possible. Experimental results conducted with a KUKALWR manipulator using two joints in planar motion, verify the validity on both methods.

Autonomous mobile robots need accurate localization techniques to perform assigned task. Radio Frequency Identification Technology (RFID) has become one of the main means to construct a real-time localization system. Localization techniques in RFID rely on accurate estimation of the read range between the reader and the tags. This paper proposes an auto-localization system for indoor mobile robot using passive RFID. The proposed system reads any three different RFID tags which have a known location. The current location can be estimated using the Time Difference of Arrival (TDOA) scheme. In order to improve the system accuracy, the proposed system fuses the TDOA scheme for the three tags. A Kalman filter is used to minimize the estimated error and predict the next location. The simulation results validate the proposed framework.

This paper presents the dynamic modeling of a 3-RPR planar parallel manipulator with three flexible intermediate links in order to investigate the effects of the intermediate links flexibility on the undesired vibrations of the end-effector. For this purpose, the intermediate links are modeled as Euler--Bernoulli beams with two types of fixed-pinned and fixed-free boundary conditions based on the assumed mode method (AMM). The equations of motion of the 3-RPR manipulator are formulated using the augmented Lagrange multipliers method in the form of differential algebraic equations (DAEs) by incorporating the elastic and rigid coordinates in the set of generalized coordinates. After defining the initial conditions and imposing external forces to the manipulator, the equations are then solved numerically using the Modified Extended Backward-Differentiation Formula Implicit (MEBDFI) approach. Comparison of the simulation results for two different boundary conditions shows clearly the effects of flexibility of the intermediate links on the vibration of the end-effector trajectory. Results of this work can be used for the dynamic modeling of other manipulators or to design a controller for reducing the undesired vibrations.

In this paper we propose new tuning conditions for three saturated nonlinear proportional-integral-derivative (PID) global regulators with bounded torques for robot manipulators, which have been presented previously in the literature. The motivation of this work relies on the fact that the tuning conditions presented previously in the literature for assuring global asymptotic stability are so restrictive that it had been impossible, until now, to carry out experimental tests. New tuning criteria of unsaturated PID controllers for robot manipulators with stability conditions more relaxed than those presented previously in the literature have been proposed recently in some works by the authors. This was achieved by setting the stability conditions as expressions that have to be satisfied at each joint instead of general conditions for the whole robot. Based on this idea, we now obtain stability conditions for saturated global PID controllers which are so relaxed that they have allowed to perform, by the first time, experimental tests using controller gains which completely satisfy the proposed stability conditions. The results of such experiments are presented in this paper, where we have used a two-degrees-of-freedom robot manipulator.

In this research work, the maximum Cartesian workspace of a Tricept parallel robot with two rotational and one translational degrees of freedom was investigated. Generally, the Cartesian workspace identifies the maximum size of a work-piece, specifying its cubic x, y and z dimensions, on which the milling machine could perform operations. However, the workspace of a robot can be considered in its task space, such as ψ × θ × z for the Tricept Parallel Kinematic Mechanism (PKM). A novel homogeneous Jacobian matrix which transforms joint space velocity vector into end-effector Cartesian velocity vector has been generated named as a Cartesian Jacobian matrix. Using the indices derived from the homogeneous Cartesian Jacobian matrix, i.e. the maximum singular values and local conditioning indices, the manipulator is designed to reach the Cartesian workspace with rapid positioning rates as well as with singularity avoidance.

Mechanical regulator-free bicycle robots have lighter weight and fewer actuators than the traditional regulator-based bicycle robots. In order to deal with the difficulty of maintaining balance for this kind of bicycle robot, we consider a front-wheel drive and mechanical regulator-free bicycle robot. We present the methodologies for realizing the robot's ultra-low-speed track-stand motion, moderate-speed circular motion and high-speed rectilinear motion. A simplified dynamics of the robot is developed using three independent velocities. From the dynamics, we suggest there may be an underactuated rolling angle in the system. Our balancing strategies are inspired by human riders' experience, and our control rules are based on the bicycle system's underactuated dynamics. In the case of track-stand and circular motion, we linearize the frame's rolling angle and configure the robot to maintain balance by the front-wheel's motion with a fixed front-bar turning angle. In the case of the rectilinear motion, we linearize both front-bar steering angle and front-wheel rotating angle, and configure the system to maintain balance by the front-bar's turning with a constant front-wheel rotating rate. Numerical simulations and physical experiments are given together to validate the effectiveness of our control strategies in realizing the robot's proposed three motions.

A redundantly actuated parallel kinematic machine (PKM) can be used to avoid singularities, normalize manipulability, and increase the stiffness of anon-redundant mechanism. In this study, a redundantly actuated symmetrical PKM with five revolute (5R) joints is optimized for isotropic stiffness in the workspace. The stiffness of the 5R symmetrical PKM is calculated by the superposition of the actuator stiffness and the structural stiffness. We compared the stiffness of anon-redundant PKM and a redundant PKM. Compliance ellipses of the actuator stiffness and the structural stiffness of the non-redundant PKM resulted in the same configurations in the workspace, while those of the redundant PKM resulted in very different configurations. Optimization was performed by determining the optimal actuator torques that are needed to maximize the conditioning index. Optimal results considering structural stiffness can provide a more uniform directional stiffness than optimal results considering the index. When the strength of the linkages in a PKM is weak, the structural stiffness affects the actual stiffness considerably. We believe that the results of this study can be used to help design and control redundant PKMs.

This paper describes the design and experimental validation of an omnidirectional unmanned ground vehicle built for operation on real-world, unstructured terrains. The omnidirectional capabilities of this robot give it advantages over skid-steered or Ackermann-steered vehicles in tight and confined spaces. The robot's conventional wheels allow for operation in natural, outdoor environments as compared to omnidirectional robots that use specialized wheels with small, slender rollers and parts that can easily become obstructed with debris and dirt. Additionally, the robot's active split offset caster design allows the robot to kinematically follow continuous but non-differentiable paths and heading angles regardless of its current kinematic configuration. The active split offset caster design also results in less scrubbing torque and therefore less energy consumption during steering as compared to actively steered caster designs. The focus of this paper is the robot's mechanical design as it relates to kinematic isotropy and experimental validation of the design.

In this research, a Stewart parallel platform with rotary actuators is simulated and a prototype is tested under different operative conditions. The purpose is to make the robot robust against inertia variations considering the fact that different payloads of unknown size may be transported. Due to the complexity issued by expressing the equations of motion with independent variables, the governing equations are derived by Lagrange's method using Lagrange multipliers for imposing the kinematic constraints imposed on this parallel robot. Eliminating Lagrange multipliers by projecting the equations onto the orthogonal complement of the space of constraints, the equations of motion are transformed to a reduced form suitable for the purpose of controller design. The control approach considered here is based on a neuro-fuzzy interference method. As a first step, each revolute arm link are individually trained under different loadings and diverse maneuvers. It is purposed that once employed together, the links will have learned how to collaborate with each others for performing a common task. Training data are divided to several clusters by using a subtractive clustering algorithm. For every cluster, a fuzzy rule is derived so that the output follows the desired trajectory. In the last stage, these rules are employed by utilizing back propagation algorithms and the effectiveness of the neuro-fuzzy system becomes approved by performing multiple maneuvers and its robustness is checked under various inertia loads. The controller has ultimately been implemented on a prototype of the Stewart mechanism in order to analyze the reliability and feasibility of the method.