This paper presents a simple methodology for the quantitative and qualitative analysis of the performance of spherical parallel platforms. The quaternion formulation is used to represent the possible rotations, showing the workspace as a three-dimensional (3-D) solid object. The singularities of the platform intersect graphically with its workspace, allowing a graphical study of the mechanism kinematics. The performance criterion considered here has been the local dexterity of the manipulator. This methodology has been used to study and analyze three known orientation parallel platforms: 3-RRR, 3-UPU-wrist, and 2-UPS-1-RU. The objective of this study is to analyze the ability of these platforms to be utilized as mechanisms for the neck and shoulders of humanoid robots. Finally, the forces on actuators in some typical motions for neck and shoulder are plotted.

This investigation presents locomotion control of a hydraulically actuated six-legged humanitarian demining robot by robust adaptive fuzzy control in conjunction with the dead zone compensation technique within independent joint control framework. For proper locomotion of the demining robot, accurate tracking of the desired joint trajectory is very important. However, high degree of nonlinearity, the uncertainties due to changing hydraulic properties, and delay due to the flow of oil and dead zone of the proportional electromagnetic control valve results into an inaccurate plant model for the hydraulically actuated robotic joints. Consequently, model-based classical control techniques result into a large tracking error. Therefore, adaptive fuzzy control technique, being a model independent control paradigm for complex and uncertain systems, is a good choice for such systems. In this work, a hydraulic dead zone compensated robust adaptive fuzzy control law has been proposed for locomotion control of hydraulically actuated hexapod demining robot. The experimental results exhibit a fairly accurate trajectory tracking of the leg joints and, consequently, very stable locomotion of the walking robot.

An autonomous mobile robot operating in an unknown indoor environment often needs to map the environment while localizing within the map. Feature-based world models including line and point features are widely used by researchers. This paper presents a novel delayed-classi-fication algorithm to categorize these features using a recently developed high-performance sonar ring within a simultaneous localization and map-building (SLAM) process. The sonar ring sensor accurately measures range and bearing to multiple targets at near real-time repetition rates of 11.5 Hz to 6 m range, and uses 24 simultaneously fired transmitters, 48 receivers and multiple echoes per receiver. The proposed algorithm is based on hypothesis generation and verification using the advanced sonar ring data and an extended Kalman filter (EKF) approach. It is capable of initiating new geometric features and classifying them within a short distance of travel of about 10 cm. For each new sonar reading not matching an existing feature, we initiate a pair of probational line and point features resulting from accurate range and bearing measurements. Later measurements are used to confirm or remove the probational features using EKF validation gates. The odometry error model of the filter allows for variations in effective wheel separation required by pneumatic robot tyres. The implementation of the novel classification and SLAM algorithm is discussed in this paper and experimental results using real sonar data are presented.

In this paper, a novel contour-tracking control method of an unknown planar object by lateral force regulation for wheeled mobile robot navigation is presented. The robot is required to follow the contour of an unknown object toward the goal position. Based on mobile robot dynamic equations, a force-control algorithm is proposed to maintain constant contact with a planar object. Measured contact force from an object is used not only to regulate a contact force in a lateral direction, but also to control the orientation angle of the robot to avoid collision with an object. Simulation and experiment of contour-tracking tasks of a wheeled mobile robot are conducted. Experimental results show that the contact force is well-regulated, and the robot arrives at the goal position successfully.

In this paper, we consider the problem of rest-to-rest maneu-ver learning, via iterative learning control (ILC), for single-degree-of-freedom systems with stick-slip Coulomb friction and input bounds. The static coefficient of friction is allowed to be as large as three times the kinetic coefficient of friction. The input is restricted to be a two-pulse one. The desired input's first pulse magnitude is required to be five times the largest possible kinetic (sliding) friction force. The theory therefore allows the stiction force to be as large as the desired second input pulse. Under these conditions, we prove global convergence of a simple iterative learning controller. To the best of our knowledge, such a global-convergence proof has not been presented previously in the literature for the rest-to-rest problem with stick-slip Coulomb friction.

A characterization of singularities for a six-wire parallel architecture is presented as a result of numerical and experimental analyses. Numerical analysis has been developed through geometrical and analytical considerations. The study is based on a classification that has been derived on the basis of the geometry of tetrahedra, and singular configurations have been classified as a function of the tetrahedron volume. Experimental characterization has been carried out by considering the wire parallel architecture Cassino tracking system (CATRASYS). Experimental results are reported to characterize the performance of the CATRASYS chain in different operating conditions as an illustrative practical example.

Due to its inherent advantages such as reasoning in the format of heuristic rules based on human experience and less stringent requirement on environmental description, fuzzy logic is a promising tool for the robot motion planning in 3-dimensional dynamic environment. In general, in the Cartesian space, the variables used in characterizing the motion of a mobile robot, such as position, velocity, and force relative to other objects or coordinate frames, contain both the magnitude and the pointing information. In previous studies, the fuzzy reasoning on the pointing information was often developed based on the decomposition of the pointing vector followed by conventional fuzzy logic technique on individual vector components. Consequently, when multiple pointing variables are involved, the number of fuzzy variables that need to be considered simultaneously becomes large and the rule base may become very complex, which diminishes the advantages of the fuzzy reasoning approach. In this research, we tackle this issue by implementing a new fuzzy reasoning approach based on vector-format fuzzy variables. To achieve this, a set of new membership functions is defined for the vector-format fuzzy variables, followed by the establishment of a series of new vector-based fuzzification, fuzzy inference, and defuzzification procedures. By treating the multidimensional variables as unitary linguistic variables, the number of fuzzy variables in the fuzzy propositions and therefore the scale of the rule base can be reduced considerably. As an application example, the proposed new fuzzy reasoning approach for motion planning is applied to an Underwater Robotics Vehicle (URV) operating in an oceanic environment, where the pointing of the goal and the pointing vectors of the obstacles are treated as vector-type fuzzy variables, which leads to a compact and significantly simplified rule base. The motion planner can successfully guide the URV to move in the complicated dynamic environ-ment in a real-time fashion, which clearly demonstrates the effectiveness and robustness of the new fuzzy logic approach.

Although parallel-jaw grippers play a vital role in automated manufacturing, gripper surfaces are still designed by trial-and-error. This paper presents an algorithmic approach to designing gripper jaws that mechanically align parts in the vertical (gravitational) plane. We consider optimal edge contacts, based on modular trapezoidal segments that maximize contact between the gripper and the part at its desired final orientation. Given the n-sided 2D projection of an extruded convex polygonal part, mechanical properties such as friction and center of mass, and initial and desired final orientations, we present an O(n3 log n) numerical algorithm to design optimal gripper jaws. We also present an O(n log n) algorithm to compute tolerance classes for these jaws, and report on an online implemented version of the algorithm and physical experiments with the jaws it designed. This paper extends earlier results that generated optimal point contacts [M. T. Zhang and K. Goldberg, “Gripper point contacts for part alignment,” IEEE Trans. Robot. Autom.18(6), 902–910 (2002)].

In order to allow people to explore potential fire environments without risk of danger, a new fire scout mobile robot used in urban environments is introduced in this paper. It adapts itself to stair climbing by using articulated-chain-wheeled mobile style with differential wheels. The positive pressure with continuous flow of protected gas inside the body endows the robot with explosion protection capability. When the wireless control signal is interrupted, it could automatically return to safe place along previous path based on sensorial data. Since position estimation only using encoders reading has serious limitations as mobile robot movement proceeds, a novel method integrating data of encoders and ultrasonic sensors is built, which uses iterative closest point algorithm to do data matching so as to adjust position and orientation of the mobile robot. This path retracing method realizes high accuracy and fast speed of automatic returning when the mobile robot is working in static urban environment even if the environment is unknown.

In this paper, a velocity space method of motion planning for nonholonomic systems is presented. This method, based on Lie algebraic principles and locally around consecutive current states, plans a motion towards a goal. It is effective as most of the computations can be carried out analytically. This method is illustrated on the unicycle robot and the inverted pendulum.

The purpose of this paper is to present a robust tracking control algorithm for underactuated biped robots capable of self-balancing in the presence of external disturbances. The biped is modeled as a five-link planar robot with four actuators located at hip and knee joints. A sliding mode control law has been developed for the biped to follow a human-like gait trajectory while keeping the torso nearly upright. The control forces are calculated by defining four first-order sliding surfaces as a linear combination of the torso and the four joint tracking errors. The control approach is shown to guarantee that all trajectories will reach and stay on these surfaces during each step, while the walking cycle stability is maintained through a Lyapunov function. The criteria for asymptotic stability of the surfaces are presented and a numerical search method is implemented for the selection of the corresponding surface parameters. The paper further investigates the robustness of the controller in response to disturbances. Numerical simulations demonstrate the tracking stability of the biped's multistep walk and its human-like response to an external disturbance.

This study develops a novel image-guided robotic system that can be used to position biopsy needles or drill fixation holes. After the patient has received a CT-scan, the registration of the image, localizer (patient), and robot frames will be done by finding the optimum transformation matrix among the image and localizer coordinates of the fiducial markers and the DRFs mounted on the robot. Then, surgical paths planned on the computer displayed images can be transformed to the robot frame, and the robot is thus capable to move surgical tools to the preplanned location. The positioning error is about 2 mm and the orientation error is about 0.23°.