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In this paper, a novel soft inflatable arm is proposed for telepresence robots. The new proposed structure of the arm is achieved by a very common and low-cost inflatable material and it is very light, weighing only about 50 g. However, it can realize agile movement by driving six tiny cables installed in the shoulder and elbow joints. The soft inflatable arm can work by pumping air at a very low pressure ( $7.32 \pm 3.45$ kPa) and allows direct and soft human contact without any external force sensors. This paper proposes joint compressed models, joint kinematic models, and kinematic models for the whole inflatable robot arm. These models can be easily applied to multijoint arms. In addition, a new redundancy resolution method is also developed for the inflatable arm, which makes it easier to control resolution and is less complex than other traditional approaches. Numerous experiments have been conducted, including performances of accuracy, repeatability, motion trajectories, human-safe interaction, and remote interaction. Results are satisfactory and validate the expected performance of the proposed robotic arm.

Redundant space manipulators, including Space Station Remote Manipulator System (SSRMS), Special Purpose Dexterous Manipulator (SPDM) and European Robotic Arm (ERA), have been playing important roles in the construction and maintenance of International Space Station (ISS). They all have 7 revolute joints arranged in similar configurations, and are referred to as SSRMS-type manipulators. When a joint is locked in an arbitrary position due to some failures, a 7R manipulator degrades to a 6R manipulator. Without a spherical wrist or three consecutive parallel joints, the inverse kinematics of the 6R manipulator is very complex. In this paper, we propose effective methods to resolve the inverse kinematics for different cases of any joint locked in an arbitrary position. Firstly, configuration characteristics of the SSRMS-type redundant manipulators are analyzed. Then, an existing of closed-form inverse kinematics is discussed for locking different joints. Secondly, D–H frames and corresponding D–H parameters of the new 6-DOF manipulator formed by locking a joint in an arbitrary position are re-constructed. A unified table is then created to describe the kinematics for all possible cases of single joint locking failure. Thirdly, completely analytical and semi-analytical methods are presented to solve the inverse kinematics equations, and the former is used for locking joint 1, 2, 6 or 7 while the latter for locking joint 3, 4 or 5. Finally, typical cases for single joint locking are studied. The results verify the proposed methods.

This paper presents the gait design and comparison study of a quadruped robot. The main contributions of this paper are: (i) Explore the modularized system design of an 8 degree-of-freedom quadruped robot with a power management system. (ii) Propose a gait design method based on drive function. (iii) Propose another gait design method based on foot trajectory. (iv) The simulation of the walk and trot gaits with above-mentioned methods are validated in Webots. (v) The walk and trot gait are successfully implemented in the real robot. Experimental results show that the stable locomotion can be achieved with improved elliptical foot trajectory.

Currently, the shock absorption system for outdoor AGV is mainly built with identical-spring solution, in which all the damping springs have the identical elastic coefficient. In this paper, we introduce a method to design the shock absorption system of the AGV using dual-spring solution. Springs of two different elastic coefficients are used, and an enhanced performance in obstacle-crossing capability can be achieved. The proposed dual-spring solution design method takes several critical outdoor working requirements as design constraints, and integrates damping system analysis to determine the optimal coefficients for the dual-spring system. To validate the effectiveness of this dual-spring design method, theoretical analysis is fully derived and a AGV chassis is physically built using dual-spring solution and is subjected to a series of validation tests.

In this paper, we propose a novel design of gaits for space manipulators so as to minimize the dynamic disturbance on a space station. Without modifying their joint configuration, we first propose the use of our previous developed gripping methodology. It combines the concepts of wheels motion in parallel grippers to reduce the swing motions in conventional gaits. For the proposed gaits, three major aspects are considered including 1) linear motion; 2) turning; and 3) exterior transition. Based on the conventional modeling approach for fixed base space manipulators, we extend the method to formulate the dynamic coupling during wheels motion. It is to visualize the manipulator as a prismatic joint with its gripping base moving with wheels motion. Also, we develop an experimental platform for verification. For disturbance analysis, various simulations have been conducted. Results have validated that the proposed gaits generate the lowest disturbance on a space station.

This paper presents an online dynamic hand gesture recognition system with an RGB-D camera, which can automatically recognize hand gestures against complicated background. For background subtraction, we use a model-based method to perform human detection and segmentation in the depth map. Since a robust hand tracking approach is crucial for the performance of hand gesture recognition, our system uses both color information and depth information in the process of hand tracking. To extract spatio-temporal hand gesture sequences in the trajectory, a reliable gesture spotting scheme with detection on change of static postures is proposed. Then discrete HMMs with Left-Right Banded (LRB) topology are utilized to model and classify gestures based on multi-feature representation and quantization of the hand gesture sequences. Experimental evaluations on two self-built databases of dynamic hand gestures show the effectiveness of the proposed system. Furthermore, we develop a human-robot interactive system, and the performance of this system is demonstrated through interactive experiments in the dynamic environment.

Ocean exploration has attracted enormous interest from human-kind for thousands of years. The sailing boat, propelled by wind is a historical invention. But human-involved marine exploration has high risk and low efficiency. This paper presents a new autonomous surface vehicle (ASV) based on retrofitting a trimaran sailing boat. The previous human-based maneuvering interfaces, i.e. sail and rudder control, are motorized by three electric actuators. The ASV acquires signals of wind speed and direction, GPS position, and rolling angle, determine the heading based on various wind direction. Experiments validates the effectiveness of the ASV.

Monocular cameras are not generally considered as a 3D measurement tool in the field of intelligent transportations. This belief limits the application of monocular cameras in many applications such as guiding robots or vehicles for autonomous driving. In this paper, we demonstrate that with the reference of a license plate, a monocular camera can be used as a tool to measure 3 dimensional parameters (width, height and length) of a passenger vehicle down to 10 cm accuracy. The proposed measurement method does not reply on any training process, but is designed as a fast and direct approach utilizing a series of fundamental computer vision techniques such as ROI extraction, edge/line detection, space coordinates transformations, etc. A series of validation tests were conducted and the results demonstrated the robustness of this measurement method and implies the possibility to broaden the application scope of monocular cameras in the field of autonomous driving and intelligent transportation systems.

Space robots are in huge demand due to the rapid growth of their service targets, i.e., spacecraft. There are generally large flexible components on spacecraft, such as antenna reflectors and solar paddles. Due to the vibratility of their structure, it is challenging for a space robot with flexible appendages (the base is then called flexible-base) to capture and repair the large flexible spacecraft. After capturing, the two spacecraft with flexible appendages are connected by a space manipulator, and a compounded system is formed. In this paper, we developed a dynamic model and a closed-loop simulation system, to provide a means to verify path planning and control algorithms. Initially, the dynamic characteristics of different capturing stages (preimpact and post-impact) were analyzed. The topologies of a flexible-base space robot and the compounded system were described based on incidence and channel matrices. Secondly, the recursive dynamics was formulated and resolved by an effective numerical method. The modeling was verified by Adams’ model. Thirdly, we implemented a dynamics calculation block in Matlab/Simulink environment using the S-function package for the C program, and developed a closed-loop simulation system, which was composed of the Planning and Controller, the Multibody Dynamic, and the 3D Display modules. Finally, based on the simulation system, two typical missions—target berthing and on-orbital manipulation of the target along a circle, were simulated and evaluated. Dynamics analysis results presented some useful rules for the path planning and control to suppress the vibration of the flexible structure.

Treebot is the first tree-climbing robot that is capable of climbing from a tree trunk to a branch. The robot employs several design principles adapted from arboreal animals, including claw gripping and inchworm locomotion, with a certain artificial optimization to achieve high maneuverability on irregular-shaped trees. Treebot is composed of a pair of tree grippers that permits Treebot to attach to a wide variety of trees with a wide range of gripping curvature, and a novel continuum maneuvering structure that provides high maneuverability and adaptability. In the robot actuation, only five actuators are necessary. Although Treebot weighs only 600 gr, it has a payload capability of 1.75 kg, which is nearly three times its own weight. This paper describes the design process and specifically addresses the robot locomotion and optimization of gripping force. Experimental results demonstrate the robot's ability to climb trees with high maneuverability. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.

Improvements in hybrid electric vehicle (HEV) fuel economy and emissions heavily depend on an efficient energy management strategy (EMS). However, the uncertainty of future driving conditions generally cannot be easily tackled in EMS design. Most existing EMSs act upon fixed parameters and cannot adapt to varying driving conditions. Therefore, they usually fail to fully explore the potential of these advanced vehicles. In this paper, a novel EMS design procedure based on neural dynamic programming (NDP) is proposed. The NDP is a generic online learning algorithm, which combines stochastic dynamic programming (SDP) and the temporal difference (TD) method. Instead of computing the utility function and optimal control actions through Bellman equations, the NDP algorithm uses two neural networks to approximate them. The weights of these neural networks are updated online by the TD method. It avoids the high computational cost that SDP suffers from and is suitable for real-time implementation. The main advantages of NDP EMS is that it does not rely on prior information related to future driving conditions, and can self-tune with a wide variance in operating conditions. The NDP EMS has been applied to “Qianghua-I”, a prototype of a parallel HEV, using a revolving drum test bench for verification. Experiment results illustrate the potential of the proposed EMS in terms of fuel economy and in keeping state of charge (SOC) deviations at a low level. The proposed research ensures the optimality of NDP EMS, as well as real-time applicability.

In this paper, a fast charging system (FCS) is designed for service robots. In this design, batteries are used to due to its energy density, whereas supercapacitors (SCs) are used to enhance the power density. DC-DC converter controls the FCS. The main advantage of the design of fast charging system is that, the SCs are charged with a large current fast and then discharge to the batteries with small current slowly. This feature is beneficial for batteries' long-life and store more energy for service robots which have been in great demand for multiple purposes, such as elderly care, child education etc. Some experimental and testing results are presented to validate the design of FCS for service robots.

In this paper, we propose an autonomous tree climbing strategy for a novel tree climbing robot that is named Treebot. The proposed algorithm aims to guide Treebot in climbing along an optimal path by the use of minimal sensing resources. Inspired by inchworms, the algorithm reconstructs the shape of a tree simply by the use of tactile sensors. It reveals how the realization of an environment can be achieved with limited tactile information. An efficient nonholonomic motion planning strategy is also proposed to make Treebot climb on an optimal path. This is accomplished by the prediction of the future shape of the tree. The study that is presented in this paper also includes the formulation of Treebot kinematics and an analysis of the workspace of Treebot on different shapes of a tree. Numerous experiments have been conducted to evaluate the proposed autonomous climbing algorithm and to unveil the ability of Treebot.

Space robotic systems are expected to play an increasingly important role in future space activities. Nevertheless, dynamics modeling and motion planning of a space robot are much more complex than those of a fixed-base robot, due to the dynamic coupling between the manipulator and its base. On the other hand, in order to assure the success of on-orbital missions, many experiments are required to verify the key algorithms on the ground before the space robot is launched. In this paper, the main research achievements on dynamics modeling, path planning, and ground verification are reviewed, and future studies are recommended. Firstly, we summarize the essential modeling concepts, and deduce the kinematics and dynamics equations of a space robot. Secondly, the main motion planning approaches are discussed. Then, different ground verification systems, including the air-bearing table, neutral buoyancy, airplane flying, free-falling motion, suspension system, and hybrid system, are introduced. Finally, the future research trends are forecasted.

Battery fast charging is one of the most significant and difficult techniques affecting the commercialization of electric vehicles (EVs). In this paper, we propose a fast charge framework based on model predictive control, with the aim of simultaneously reducing the charge duration, which represents the out-of-service time of vehicles, and the increase in temperature, which represents safety and energy efficiency during the charge process. The RC model is employed to predict the future State of Charge (SOC). A single mode lumped-parameter thermal model and a neural network trained by real experimental data are also applied to predict the future temperature in simulations and experiments respectively. A genetic algorithm is then applied to find the best charge sequence under a specified fitness function, which consists of two objectives: minimizing the charging duration and minimizing the increase in temperature. Both simulation and experiment demonstrate that the Pareto front of the proposed method dominates that of the most popular constant current constant voltage (CCCV) charge method.

This paper presents an omnidirectional steer-by-wire system for a four-wheel independent steering vehicle. The system consists of an extended steering interface and a behavior-based steering controller. The extended steering interface provides a novel manipulation way to vehicle driver. The driver can control the vehicle in traditional way or omnidirectionally without any mode switching operation. The reservation of the traditional driving way makes the driver adapt the novel steering interface easily. The steering interface also has a force-feedback function to synchronize the extended steering interface and the orientations of wheels so as to improve vehicle handling. The behavior-based steering controller is designed for controlling the orientations of wheels. It acts as virtual linkage among each wheel to minimize wheel slip resulted by the misalignment of wheels. As there is no trajectory planning needed in the control algorithm, the proposed controller is especially suitable for a nonautonomous vehicle, the driving path of which cannot be predetermined.

Space robotic systems are expected to play an increasingly important role in the future on-orbit service. The applications include repairing, refueling or de-orbiting of a satellite, or removal of the space debris. The dynamical performances of space robotic system result from the multi-physics interactions between mechanical, electrical, electronic, control, etc. In this paper, we developed a unified multi-domain modelling and simulation system. The system is composed of the following modules: the path planner, joint controllers, motor and its driver, gearing mechanism of the space manipulators, the Guidance, Navigation, and Control (GNC) system, the actuators of the base, and the orbital environment, orbital dynamic and the multi-body dynamic of the whole system, etc. Based on this system, the operation during different stages, including far range rendezvous, close range rendezvous (is usually divided into two sub-phases: closing and final approach) and target capturing can be studied from the view of multi-physics domains. The key algorithms, such as pose (position and attitude) measurement, GNC of the base, path planning and control of the space manipulator, and so on, can be validated using the system. As examples, the capturing processes of a moving target under free-floating and attitude-controlled modes are simulated and the simulation results are given.

In this paper, we present an innovative design of a solder paste inspection system that can be practically integrated into existing solder paste printing machines. Since solder paste inspection systems usually occupy a large vertical space, we designed a mirror box that can redirect the transmission of fringe patterns. In this way, a new parallel-structure solder paste inspection system with a significant reduction in the vertical constraint is developed. We also developed a hybrid weighting algorithm that applies the distance and fringe contrast to acquire the height of solder pastes. Furthermore, we developed an algorithm that generates the 2-D image from the fringe pattern images during the four-step algorithm. It reduces the time required for solder paste inspection compared to traditional approaches that use special lighting systems to create the 2-D image. Based on the results of the height acquisition algorithm, 2-D and 3-D solder paste inspections are performed. Experimental results show that our system can inspect a 20 mm times 20 mm printed circuit board area within 2 s to detect common 2-D and 3-D defects, and the maximum standard deviation for the average height is 3 mum.

SUMMARYThe technologies of autonomous rendezvous and robotic capturing of non-cooperative targets are very crucial for the future on-orbital service. In this paper, we proposed a method to achieve this aim. Three problems were addressed: the target recognition and pose (position and attitude) measurement based on the stereo vision, the guidance, navigation and control (GNC) of the chaser, and the coordinated plan and control of space robot (CP&C). The pose measurement algorithm includes image filtering, edge detection, line extraction, stereo match and pose computing, et al. Based on the measured values, a certain GNC algorithm was designed for the chaser to approach and rendezvous with the target. Then the CP&C algorithm, which is proved to be advantageous over the traditional separated method, was used to plan and track the trajectories of the base pose and the joint angle. At last, a 3D simulation system was developed to evaluate the proposed method. Simulation results verified the corresponding algorithms.

For the aging population, surveillance in household environments has become more and more important. In this paper, we present a household robot that can detect abnormal events by utilizing video and audio information. In our approach, moving targets can be detected by the robot using a passive acoustic location device. The robot then tracks the targets by employing a particle filter algorithm. To adapt to different lighting conditions, the target model is updated regularly based on an update mechanism. To ensure robust tracking, the robot detects abnormal human behavior by tracking the upper body of a person. For audio surveillance, Mel frequency cepstral coefficients (MFCC) is used to extract features from audio information. Those features are input to a support vector machine classifier for analysis. Experimental results show that the robot can detect abnormal behavior such as "falling down" and "running". Also, a 88.17% accuracy rate is achieved in the detection of abnormal audio information like "crying", "groan", and "gun shooting". To lower the false alarms by abnormal sound detection system, the passive acoustic location device directs the robot to the scene where abnormal events occur and the robot can employ its camera to further confirm the occurrence of the events. At last, the robot will send the image captured by the robot to the mobile phone of master.

Space robots are playing an increasingly important role in on-orbital servicing, including repairing, refueling, or de-orbiting the satellite. The target must be captured and berthed before the servicing task starts. However, the attitude of the base may lean much and needs re-orientating after capturing. In this paper, a method is proposed to berth the target, and re-orientate the base at the same time, using manipulator motion only. Firstly, the system state is formed of the attitude quaternion and joint variables, and the joint paths are parameterized by sinusoidal functions. Then, the trajectory planning is transformed to an optimization problem. The cost function, defined according to the accuracy requirements of system variables, is the function of the parameters to be determined. Finally, we solve the parameters using the particle swarm optimization algorithm. Two typical cases of the spacecraft with a 6-DOF manipulator are dynamically simulated, one is that the variation of base attitude is limited; the other is that both the base attitude and the joint rates are constrained. The simulation results verify the presented method.

In this paper, we discuss the problem of how human control strategy can be represented as a parametric model using a support vector machine (SVM) and how an SVM-based controller can be used in controlling dynamically stable systems. The SVM approach has been implemented in the balance control of Gyrover, which is a dynamically stable, statically unstable, single-wheel mobile robot. The experimental results that compare SVM with general artificial neural network approaches clearly demonstrate the superiority of the SVM approach with regard to human control strategy learning.

Space robotic systems are expected to play an increasingly important role in the future. The robotic on-orbital service, whose key is the capturing technology, becomes research hot in recent years. In this paper, the authors propose an autonomous path planning method for target capturing. The task is described in Cartesian space and it can drive the manipulator to approach the target along the closest path. Firstly, the target feature is extracted based on the measured information via the hand-eye camera, and the target pose (position and orientation) and velocities (linear velocity and angular velocity) are estimated using Kalman filtering technology. Then, a numerically feasible approach is presented to plan the manipulator motion and avoid the dynamic singularities, which are transformed into real-time kinematic singularities avoiding problem. Thirdly, the potential disturbance on the base due to the manipulator's motion is estimated, and the joint rates are autonomously adjusted to reduce the disturbance if it is beyond the allowed bound. At last, a ground experiment system is set up based on the concept of dynamic emulation and kinematic equivalence. With the experiment system, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm.

With the emerging need for household applications, service robotics has become a hot spot attracting researchers globally. Universities, institutes, and industrial companies, either independently or collaboratively, have been focusing on research and development for household service robots, resulting in interesting and well-performing household service robotic systems. In this chapter, we first give a categorization of the various applications, followed by an elaboration of some highlighted cases with their overall system designs.

Household service is one of the most important fields in robot applications. Compared with applications in industry, the household environment is more challenging. First, the household environment is usually unstructured, which makes it more difficult to handle simple tasks such as what the assembly line robot can easily achieve. Second, the object for household services is human, sometimes a small child. For safety reasons, the robot should be very careful when taking actions. Third, the household robot is expected to be cleverer in dealing with complicated situations, which requires flexibility in responding. All these challenges are, to some extent, related to the capability of perceiving various objects, from an old table to a sleeping baby. In this chapter, we discuss the state of the art in object recognition for household service.

Human–robot interaction (HRI) studies on how humans collaborate and interact with robots in an effective and natural way have received considerable attention in the robot research community, especially with regard to the design and development of household service robots, owing to their highly interactive characteristics in domestic service activities. Many researchers have proposed a variety of principles, algorithms, and systems to achieve an effective and natural HRI in the domestic environment. In this chapter, we first give a brief illustration of the state of the art for HRI, divided into several categories, and then elaborate on some selected cases with regard to the design and implementation of HRI systems.

Robotic grasping and manipulation comprise three subtasks, i.e., target detection, planning, and control. The robot first needs to detect the target. Here “detect” means to find (or recognize) the target and locate it. The target could be the object to be manipulated (e.g., electrical plugs) or the destination of the object (electrical sockets). Then the robot approaches the target in an optimized trajectory. In the process of approaching and grasping, the robot should be controlled to perform the task correctly and smoothly. In this chapter, we review the approaches to accomplish these three subtasks, i.e., target detection, planning, and control.

In this chapter, an efficient and low-cost cellphone-commandable mobile manipulation system is described. Aiming at home use and elderly caring, this system can be easily commanded through a common cellphone network to efficiently grasp objects in a household environment, utilizing several low-cost off-the-shelf devices. Unlike the visual servo technology using a high quality vision system with the associated high cost, the household-service robot would not be able to afford such a high quality vision servo system, and thus it is essential to use some low-cost devices. However, it is extremely challenging to create such a vision system with precise localization, as well as motion control. To tackle this challenge, we developed a real-time vision system with which a reliable grasping algorithm combining machine vision, robotic kinematics and motor control technology is presented. After the target is captured by the arm camera, the arm camera keeps tracking the target while the arm keeps stretching until the end effector reaches the target. However, if the target is not captured by the arm camera, the arm will make a move to help the arm camera capture the target under the guidance of the head camera. This algorithm is implemented on two robot systems: one with a fixed base and another with a mobile base. The results demonstrate the feasibility and efficiency of the algorithm and system we developed, and our study shows the significance of developing a service robot in a modern household environment.

With the significant development of robotic technologies, the applications of robots have been extended broadly from their traditional industry role to military, medical field, and even daily services. Robotics has gradually become a very large industry with tremendous influence on the sustainable development of the world.

Technology for the capturing of space target is very important for on-orbit servicing. In order to assure the task is accomplished successfully, ground experimentations are required for the verification of the planning and control algorithms of space robotic system before it is launched. In this paper, an experiment concept is used, which is a hybrid approach, i.e. it combines the mathematical model with the physical model. The key issues of the concept are dynamic emulation and kinematic equivalence, in which the behaviors of the space robotic system are calculated by its dynamic equations. The motion of its end-effector and the space target is realized by two industrial robots. According to different observation spots, two modes of capturing process are emulated: one is observed from the inertial frame, the other is from the space base. Based on the concept proposed above, a ground experiment system is set up, which is composed of two industrial robots, a set of global visual system and five industrial computers. Using the system, algorithms of space robot of any geometry and mass properties can be tested. As an example, the autonomous trajectory planning algorithm is verified by the experiment of capturing a moving target. Moreover, a real-time 3D simulation system is developed to emulate the capturing process in 3D space. Numeric simulation and experiment results show that the ground system is effective in evaluating the planning and control algorithms of space robot.

To provide a high starting torque and to work under a high rpm range are the design requirements for the integrated startgenerators (ISG) used for intelligent vehicles with hybrid powertrains. However, meeting with both of these two requirements usually involves with sophisticated motor and controller design and high manufacturing cost. Hence, a transmission with variable reduction ratio is desired to be configured between the ISG and the engine. In an earlier paper, a Controller-Free Ratio-Variable gearbox design concept has been introduced, which can auto change gear ratios in a purely mechanical way and avoid from using any controller or actuators. This paper represents the work on implementation, testing and evaluation of the gearbox. The performance of the gearbox proof to be functional though the test result.

Recently, the control of telepresence robots is still a challenge for researchers. In this paper, we propose a method to realize a more natural assisted navigation for telepresence robots during teleoperation. Different from existing approaches, the proposed method utilizes an omni-directional chassis which is realized by a three wheels drive (3WD) mechanism. Without using any expensive 3D sensing equipments, our proposed method is realized by using only low cost ultrasonic sensors. To increase the sensing frequency, we propose a new sensing method for the ultrasonic sensors. To generate the avoidance motions, Potential Field (PF) method is applied. Different from conventional approach, obstacle avoidance motions are realized naturally through linear translations. With this method, the robot's orientation can be maintained which improves user experience and allows a more user-friendly teleoperation. To evaluate the proposed method, it has been implemented on our previous developed telepresence robot, called ‘T-robot’. Results show that the PF method helps reduce the teleoperated time with no collisions and user intervention. Also, a more natural movement and user friendly control is achieved.

Electronic devices (PCs, smart phones, etc.) are ubiquitous in the world and the convenience in users' input has become increasingly important for their extensive applications. Disabled armless people are also in need of a novel input interface for a better life. In this paper, we present our research on a wearable sensor-integrated shoe system as a writing platform, by sensing and analyzing the foot movement, so it enables people to write by foot. Also using this system, people can exercise their lower limbs and related brain parts for recovery from illness, e.g. stroke. We use the force sensors (FSRs) to localize the foot when it attacks ground, i.e. touching ground from air. This system classifies FSRs data by BP neural network to obtain the start point for each basic stroke. Also the force sensor can classify the location of stroke starting point from another aspect. Finally, low cost optical tracking sensor is used to draw the stroke. Experiments validate the design of the shoe writing system.

Global manufacturing chains have become common in the 21st century. To perform remote monitoring and diagnosis in such chains, real-time data compression has become a core factor in the efficient and effective exchange of information via computer networks. This paper presents a new technique for compressing data using a kernel-based method. Overcoming the drawbacks of support vector techniques – that is, fast decompression but slow compression – the new method exhibits high speed in both phases. In addition, the new method can also be applied for pattern classification. Based on strain signal, example tests derived from sheet metal stamping operations, the new method is shown to be very effective. The proposed technology has enormous potential in the application of advanced manufacturing processes monitoring and control through Internet or Intranet.

We have developed a single wheel, gyroscopically stabilized robot. This is a novel concept for a mobile robot that provides dynamic stability for rapid locomotion. The robot is a sharp-edged wheel actuated by a spinning flywheel for steering and a drive motor for propulsion. The spinning flywheel acts as a gyroscope to stabilize the robot and it can be steered by tilting. This robot is nonholonomic in nature, underactuated and inherently unstable in the lateral direction. In this paper, we first develop a three-dimensional (3-D) nonlinear dynamic model and investigate the dynamic characteristics of the robot. We conduct simulations and real-time experiments to verify the model. Both simulations and experiments show that the flywheel has a significant stabilizing effect on the robot. Then, we can decouple the longitudinal and lateral motions of the robot by linearization. We propose a linear state feedback to stabilize the robot at different lean angles, so as to control the steering velocity of the robot indirectly, because the robot steers only by leaning itself to a predefined angle. For the task of path following, we design a controller for tracking any desired straight line without falling. In the controller, we first design the linear and steering velocities for driving the robot along the desired straight line by controlling the path curvature. We then apply the linear state feedback to stabilize the robot at the predefined lean angle such that the resulting steering velocity of the robot converges to the given steering velocity. This work is a significant step toward fully autonomous control of such a dynamically stable but statically unstable system.

Sensor signals produced in industrial manufacturing processes contain valuable information about the condition of operations. However, extracting the appropriate feature for effective fault diagnosis is difficult. Moreover, the adaptability and flexibility of current fault diagnosis systems are often found wanting in real-world applications. Unfortunately, it is essential to rebuild most fault diagnosis systems when new fault types emerge. This paper presents an intelligent fault diagnosis system based on a hidden Markov model. Introducing the concepts of time marginal energy and frequency marginal energy, the features of which can be acquired by the wavelet packet technique satisfy the requirements for fault diagnosis. By utilizing the best tree principle, this method not only extracts the feature automatically without a priori experience but also compresses the data; both of which ensure a system that is practical for real-time application. The new diagnosis system developed here is efficient and effective, as demonstrated by the model developed and applied to a real-time sheet metal stamping process. Based on tests conducted during two experiments (one based on simple blanking, the other on progressive operations) and related comparisons, the proposed method is substantially more effective than other approaches. In addition, the new method requires that only related models be created for new fault types, which results show are ideal for shop floor applications.

This paper presents a new method for fault diagnosis using a newly developed method, support vector machine (SVM). First, the basic theory of the SVM is briefly reviewed. Next, a fast implementation algorithm is given. Then the method is applied for the fault diagnosis in sheet metal stamping processes. According to the tests on two different examples, one is a simple blanking and the other is a progressive operation, the new method is very effective. In both cases, its success rate is over 96.5%. In comparison, the success rate of the popular artificial neural network (ANN) is just 93.3%. In addition, the new method requires only few training samples, which is an attractive feature for shop floor applications.

Manufacturing system is becoming larger and more complicated. Global manufacturing chains have become common in the new millennium. Internet and intranet integrate the advanced manufacturing system. To perform remote monitoring and diagnosis in such chains and systems, real-time data compression has become a core factor in the efficient and effective exchange of information exchange via computer networks. This paper presents a new technique for compressing data using a kernel-based method. Overcoming the drawbacks of support vector techniques — that is, fast decompression but slow compression — the new method exhibits high speed in both phases. In addition, the new method can also be applied for pattern classification. Based on strain signal example tests derived from sheet metal stamping operations, the new method is very effective. The proposed technology has enormous potential in the application of advanced manufacturing system monitoring and control through internet or intranet.

Finite-time control of the robot system is studied through both state feedback and dynamic output feedback control. The effectiveness of the proposed approach is illustrated by both theoretical analysis and computer simulation. In addition to offering an alternative approach for improving the design of the robot regulator, this research also extends the study of the finite-time control problem from second-order systems to a large class of higher order nonlinear systems.

The fault diagnosis is important in continuously monitoring the performance and quality of manufacturing processes. Overcoming the drawbacks of threshold approach, artificial neural network may extract the symptom of the faults through learning from the samples, but it is difficult to design its structure. Moreover, it needs a large numbers of samples in practice. In this paper, support vector machine approach was proposed to overcome these limitations based on statistics learning theory, and a new fault diagnosis system is developed. The experimental results showed that it is an efficient and practical on-line intelligent monitoring system for the stamping processes.

This paper presents a new design for the grippers of Treebot, a novel tree climbing robot that can move from trunks to branches. As trees are unstructured environments, grippers can easily become embedded in the barks. To reduce these occurrences and enhance Treebot's robustness, we designed a retractable spine with increased withdrawal force. Here, we analyze the relationship between the insertion and adhesion forces of the tips using data from a large number of experiments. The magnitude of the withdrawal force of the previous gripper is calculated using kinematic analysis. By comparing the expected and actual forces, we assess the advantages of retractable spine. The results of these structural analyses and simulations demonstrate the feasibility of the new retractable spine.

Localization of an autonomous mobile robot has always been a topic of interest in Robotics community. The constraints of working under different environments are constantly a challenge in designing an efficient localization system. We propose a localization algorithm for a mobile robot, which will be used for home security. The objective is to perform indoor localization efficiently and keeping the cost as low as possible so as to make it commercializable. Here, we introduce an approach based on recognizing a pattern generated by laser pointers on the wall, which is captured by an infrared camera. The image of this pattern is used to locate the position of a robot in the room. The problem of working under black ceiling has been overcomed because the projection is on the wall and is moving which also increases the range of operation. As the pattern is unique, the interference of strong sunlight has also been fixed to some extent. Experimental results show that the proposed approach is effective in real environment and opens new doors for future research.

A single wheel, gyroscopically stabilized robot was developed to provide a dynamic stability for rapid locomotion. It is a sharp-edged wheel actuated by a spinning flywheel for steering and a drive motor for propulsion. The spinning flywheel acts as a gyroscope to stabilize the robot and it can be tilted to achieve steering. Its nature is nonholonomic, underactuated and inherently unstable in the lateral direction. In this paper, we discuss the problem of controlling the tilt-up motion of such a dynamically stable but statically unstable robot. We first present a dynamic model which is verified through simulations and experiments. Then, we develop a model-based controller for tilt-up motion, assuming that the robot is rolling without slipping. Taking advantage of human skill in teleoperating the robot, we develop a human-based controller for tilt-up motion, in which we train a human control strategy model to abstract the operator’s skill in controlling the tilt-up motion. The controller was successfully implemented, such that the robot can recover from fall automatically. This work is a significant step towards a fully automatic control of such a dynamically stable but statically unstable robot.

This paper presents a novel Differential Modular Robot Joint (DMRJ), which has high payload capability and low weight. The ratio between the output torque and the reducer's weight is 178.3 Nm/kg, which is the highest value we have known. The DMRJ is designed modularly for high payload tasks and can be attached to robots as arms or legs. Two high power DC brush motors are applied to drive the differential mechanism, which can rotate in two degrees of freedom (DOF) and has a minimal size. A control algorithm for the DMRJ has been devised in accordance with the kinematic and mechanical analysis. A prototype of the DMRJ has been manufactured, and the effectiveness of the control algorithm has been verified by several experiments. Thanks to its excellent performance, the DMRJ can be widely utilized in many robotic applications.

Combining functions with aesthetics, characters with drawings, Chinese calligraphy is a unique type of traditional art in China. To mimic the special writing skills, we develop a calligraphy robot which consists of one 6-DOF robot arm, one linear rail and one paper conveyor. This calligraphy robot, called Callibot, has several features. Firstly, it has sufficient degrees of freedom and very few singularities which improve the manipulability of the robot. Secondly, Callibot could mimic real motion of human writing because playback from demonstration approach is adopted. The encoders will record the joint positions while demonstrating. Then Callibot filters out the noises (error readings in serial port communication) and repeats the motion. Thirdly, the workspace of the robot arm is largely expanded due to the linear rail and the paper conveyor. The experimental results show that Callibot is capable of writing a large piece of aesthetic calligraphic work.

This paper presented a novel power transmission lines inspecting robot named “Linebot”, which has high maneuverability and keeps in compact size and lightweight. Linebot has 11 degrees of freedom totally. It equips with two open-close wheels and a pair of grippers, which can be driven separately. As a result, there are three main types of motions to overcome the obstacles on the lines more efficiently. Prototype of Linebot has been developed for further research. It is composed of two parts connected by a pitch joint. Each part contains an open-close assembly, friction adjustment mechanism, grippers, pitch control mechanism, which can be controlled separately. The desired motion can be obtained by appropriate control of the drive cells. The prototype of Linebot had been developed and some experiments had been done to validate the robot's motions.

In this paper, a novel precise pick and place device (PPD) is proposed for robotic manipulators. It is capable of accurately picking the work pieces and placing them when they are deviated from their initial taught picking positions. In addition, a new muti-line identification algorithm is also developed, which is very effective, especially when the obtained data is limited but needs precise identification. Moreover, the design and implementation of PPD are developed, including hardware design, control algorithm, muti-line fitting approach, offsets calculation and compensation of inverse kinematics, etc. The advantages of PPD are low cost, effective algorithm with high accuracy, when compare with vision or other traditional approaches. Numerous pick and place experiments have been conducted and the results are satisfied.