This paper discusses about auto-laydown robot (ALR), which is applied to performing the laydown process of a solar module on earth. The robot consists of an adhesive dispensing mechanism, an auto-laydown mechanism, a pneumatic system and a control system. The method of gripping solar cells is described based on pneumatic technology. Meanwhile, a new method of controlling adhesive thickness and area during dispensing is proposed in this paper. The robot realizes the automatic laydown process of solar modules and can control the laydown pressure effectively. Compared with the manual method, the robot could control the dispensing volume and the adhesive area between solar modules and panel substrates, by means of experiments. The novel ALR greatly improves the laydown quality of solar modules and meets the lightweight trend of solar cells development.

To obtain specifications for a tactile display that would be effective in virtual reality and tele-existence systems, we have developed two types of matrix-type experimental tactile displays. One is for virtual figures (display A) and the other is for virtual textures (display B). Display A's pad has a 4 × 6 array of stimulus pins, each 0.8 mm in diameter. Three pad configurations, in which distances between any two adjacent pins (pin pitch) are 1.2, 1.9, or 2.5 mm, were developed to examine the influence of distance on a human operator's determination of virtual figures. Display B has an 8 × 8 array of stimulus pins, each 0.3 mm in diameter and with 1-or 1.8-mm pin pitch, because presentation of virtual textures was presumed to require a higher pin density. To establish a design method for these matrix-type tactile displays, we performed a series of psychophysical experiments using displays A and B. By evaluating variations in the correct answer percentage and threshold caused by different pin arrays and different pin strokes, we determined under what conditions the operator could best feel the virtual figures and textures. The results revealed that the two-point threshold should be adopted as the pitch between pins in the design of the tactile display, that a pin stroke should exceed 0.25 mm, and that the adjustment method is the most appropriate to evaluate the capabilities of tactile displays. Finally, when we compared the virtual texture with the real texture, we found that the threshold for the real texture is almost 1/3rd that of the virtual texture. This result implies that it is effective to present variations in patterns caused by rotation and variation in shearing force, itself produced by relative motion between the finger surface and object surface.

The paper introduces a family of three-DOFs translational-rotational Parallel-Kinematics Mechanisms (PKMs) as well as the mobility analysis of such family using Lie-group theory. Each member of this family has two-rotational one-translational DOFs. A novel mechanism is presented and analyzed as a representative of that family. The use and the practical value of that modular mechanism are emphasized.

Mobile manipulation involves the most important key issue in robotics: integration. While hardware integration seems to be nearly solved due to the increasing dominance of PC-compatible systems, software integration is still a challenge, since a lot of issues arise with the variety of operating systems, device drivers, application libraries, and programming languages which need to be merged in any real-world robotic system. This paper presents a software architecture, which seamlessly integrates robot arms, mobile bases, vision systems and sensing devices, in a distributed, homogeneous agent framework. Based on the Java platform, the agent-based architecture allows great flexibility in the integration of components, and provides a simple yet extensible and powerful software layer to develop further mobile manipulating environments. Detailed software issues, as well as preliminary results are shown, which pave the way towards the development of network-ready applications involving mobile and manipulating artifacts.

This study addresses the problem of adaptive controlling of both a nonredundant and a redundant robotic manipulator with state-dependent constraints. The task of the robot is to follow a prescribed geometric path given in the task space, by the end-effector. The aforementioned robot task has been solved on the basis of the Lyapunov stability theory, which is used to derive the control scheme. A new adaptive Jacobian controller is proposed in the paper for the path following of the robot, with both uncertain kinematics and dynamics. The numerical simulation results carried out for a planar redundant three-DOF (three degrees of freedom) manipulator whose end-effector follows a prescribed geometric path given in a two-dimensional (2D) task space, illustrate the trajectory performance of the proposed control scheme.

In this paper, we investigate the problem of measuring the shape of a continuum robot manipulator using visual information from a fixed camera. Specifically, we capture the motion of a set of fictitious planes, each formed by four or more feature points, defined at various strategic locations along the body of the robot. Then, utilizing expressions for the robot forward kinematics as well as the decomposition of a homography relating a reference image of the robot to the actual robot image, we obtain the three-dimensional shape information continuously. We then use this information to demonstrate the development of a kinematic controller to regulate the manipulator end-effector to a constant desired position and orientation.

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)].

We address general filtering problems on the Euclidean group SE(3). We first generalize, to stochastic nonlinear systems evolving on SE(3), the particle filter of Liu and West for simultaneous estimation of the state and covariance. The filter is constructed in a coordinate-invariant way, and explicitly takes into account the geometry of SE(3) and P(n), the space of symmetric positive definite matrices. Some basic results for bilinear systems on SE(3) with linear and quadratic measurements are also derived. Three examples—GPS attitude estimation, needle tip location, and vision-based robot end-effector pose estimation—are presented to illustrate the framework.

Over the past several decades, a number of O(n) methods for forward and inverse dynamics computations have been developed in the multibody dynamics and robotics literature. A method was developed by Fixman in 1974 for O(n) computation of the mass-matrix determinant for a serial polymer chain consisting of point masses. In other of our recent papers, we extended this method in order to compute the inverse of the mass matrix for serial chains consisting of point masses. In the present paper, we extend these ideas further and address the case of serial chains composed of rigid-bodies. This requires the use of relatively deep mathematics associated with the rotation group, SO(3), and the special Euclidean group, SE(3), and specifically, it requires that one differentiates real-valued functions of Lie-group-valued argument.

Inspired by the agility of animal and human locomotion, the number of researchers studying and developing legged robots has been increasing at a rapid rate over the last few decades. In comparison to multilegged robots, single-legged robots have only one type of locomotion gait, i.e., hopping, which represents a highly nonlinear dynamical behavior consisting of alternating flight and stance phases. Hopping motion has to be dynamically stabilized and presents challenging control problems. A large fraction of studies on legged robots has focused on modeling and control of single-legged hopping machines. In this paper, we present a comprehensive review of developments in the field of single-legged hopping robots. We have attempted to cover development of prototype models as well as theoretical models of such hopping systems.

The WiRo-6.3 is a six-degrees of freedom (six-DOF) robotic parallel structure actuated by nine wires, whose characteristics have been thoroughly analyzed in previous papers in reference. It is thought to be a master device for teleoperation; thus, it is moved by an operator through a handle and can convey a force reflection on the operator's hand. A completely new method for studying the workspace of this device, and of virtually any nine-wire parallel structure actuated by wire is presented and discussed, and its results are given in a graphical form.

This research focuses on the issue of dynamic modeling and controlling a robotic manipulator attached to a compliant base. Such a system is known under the name macro–micro system, characterized by the number of control actuators being less than the number of state variables. The equations of motion for a two-link planar elbow arm mounted on an oscillatory base has been presented in this investigation. In order to study the sensitivity of tuning the PID parameters to achieve the desired performance, the Grey relational analysis has first been proposed. Therefore, the aim of this work is to apply Grey theory to optimize parameters for partial states feedback of a PID controller for such a structure. The experimental results of the proposed methodology also show that it is technically and economically feasible to develop a low-cost, reliable, automatic, less time-consuming controller for robotics mounted on oscillatory bases.

Mobile robotic manipulators can augment the strength and dexterity of human operators in unstructured environments. Here, the control system for a six degree-of-freedom heavy-lift mobile manipulator for lifting and inserting payloads on the deck of a ship is described. The robotic hardware and the application present several control challenges, including structural resonances, high joint friction that varies with time, limited sensors for measuring the joint friction, complex interaction with the environment, tight tolerances for the insertion tasks, lack of bilateral force feedback of the contact forces, and ship motions. The control system enables an operator to perform insertion tasks using feedback of tactile clues of the manipulator position, and reduces the effects of friction with a combination of sensor-based, adaptive, and model-based methods of friction compensation. The control architecture is validated in simulation and on a laboratory manipulator.

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 Neural-Network- (NN) based guidance methodology is proposed for the high-precision docking of autonomous vehicles/platforms. The novelty of the overall online motion-planning methodology is its applicability to cases that do not allow for the direct proximity measurement of the vehicle's pose (position and orientation). In such instances, a guidance technique that utilizes Line-of-Sight- (LOS) based task-space sensory feedback is needed to minimize the detrimental impact of accumulated systematic motion errors. Herein, the proposed NN-based guidance methodology is implemented during the final stage of the vehicle's motion (i.e., docking). Systematic motion errors, which are accumulated after a long-range motion are reduced iteratively by executing corrective motion commands generated by the NN until the vehicle achieves its desired pose within random noise limits. The proposed guidance methodology was successfully tested via simulations for a 6-dof (degree-of-freedom) vehicle and via experiments for a 3-dof high-precision planar platform.

This paper presents an approach to reduce the technical complexity of a service robotic system by means of systematic and well-balanced user-involvement. By taking advantage of the user's cognitive capabilities during task execution, a technically manageable robotic system, which is able to execute tasks on a high level of abstraction reliably and robustly, emerges. For the realisation of this approach, the control architecture MASSiVE has been implemented, which is used for the control of the rehabilitation robot FRIEND II. It supports task execution on the basis of a priori defined and formally verified task-knowledge. This task-knowledge contains all possible sequences of operations as well as the symbolic representation of objects required for the execution of a specific task. The seamless integration of user interactions into this task-knowledge, in combination with MASSiVE's user-adapted human–machine interface layer, enables the system to deliberately interact with the user during run-time.

This paper describes the methods applicable to the modeling and control of mechanical contact, particularly those systems that experience uncertain stick/slip phenomena. Geometric kinematic reductions are used to reduce a system's description from a second-order dynamic model with frictional disturbances coming from a function space to a first-order model with frictional disturbances coming from a space of finite automata over a finite set. As a result, modeling for purposes of control is made more straight-forward by getting rid of some dependencies on low-level mechanics (in particular, the details of friction modeling). Moreover, the online estimation of the uncertain, discrete-valued variables has reduced sensing requirements. The primary contributions of this paper are the introduction of a simplifying representation of friction and formal tests for kinematic reducibility. Results are illustrated using a slip-steered vehicle model and an actuator array model.

Robotic manipulators that have interacted with uncalibrated environments typically have limited positioning and tracking capabilities, if control tasks cannot be appropriately encoded using available features in the environments. Specifically, to perform 3-D trajectory following operations employing binocular vision, it seems necessary to have a priori knowledge on pointwise correspondence information between two image planes. However, such an assumption cannot be made for any smooth 3-D trajectories. This paper describes how one might enhance autonomous robotic manipulation for 3-D trajectory following tasks using eye-to-hand binocular visual servoing. Based on a novel encoded error, an image-based feedback control law is proposed without assuming pointwise binocular correspondence information. The proposed control approach can guarantee task precision by employing only an approximately calibrated binocular vision system. The goal of the autonomous task is to drive a tool mounted on the end-effector of the robotic manipulator to follow a visually determined smooth 3-D target trajectory in desired speed with precision. The proposed control architecture is suitable for applications that require precise 3-D positioning and tracking in unknown environments. Our approach is successfully validated in a real task environment by performing experiments with an industrial robotic manipulator.

This paper presents a simple numerical method for forward kinematics of general Stewart–Gough platforms, which can generate a unique solution directly. This method utilizes the trivial nature of the inverse kinematics of parallel manipulators, and derives a straightforward linear relationship between the small change in joint variables (leg lengths) and the resulting small motion of the platform. The solution to the forward kinematics is then achieved through a series of small changes in joint variables. Numerical examples validate and confirm the efficiency of the method.

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.