Search

Polymer coatings having high amounts of renewable carbon and self-healing properties are highly sought after in a sustainability perspective. We report here the development of bio-/CO2-derived noni...

In atomic force microscopy (AFM)-based nanomanipulation, the tip position uncertainties still exist due to the parameter inaccuracies in the open-loop compensation of the piezo scanner, the noise in the closed-loop control and thermal drift. These spatial uncertainties are very challenging to be directly estimated owing to the lack of real-time feedback, and its effects are more significant in performing an automatic nanomanipulation/assembly task than macro world manipulations. In this paper, we propose a stochastic framework for feature-based localization and planning in nanomanipulations to cope with these uncertainties. In the proposed framework, some features in the sample surface are identified to calculate their positions in statistics, and detected by using the AFM tip as the sensor itself through a local scan-based motion. In the localization, the Kalman filter is used through incorporating the tip motion model and the local scan-based observation model to estimate the on-line tip position in the task space. The simulation and experiments about tip positioning are carried out to illustrate the validity and feasibility of the proposed algorithm. Then, positioning tip for effective nanomanipulation is presented by using several experiments. Finally, a carbon nanotube is followed to show that the proposed method can provide a great potential for improving the position accuracy. Note to Practitioners —Atomic force microscopy (AFM)-based nanomanipulation has become a promising approach in developing devices and structures at nanoscale. One of the prerequisites for the effective and successful nanomanipulation is that the AFM tip position relative to the interest region can be controlled accurately. This paper proposes a stochastic approach for feature-based localization and planning method to solve these problems. The uncertainties of the tip position are decreased by using the Kalman filter method in the localization procedure. Fifty times of experiments are represented to illustrate the effectiveness and efficiency of the tip positioning method. Then, basic nanomanipulations in the vertical direction without and with SAFLP method are performed for representing significance of positioning the tip. Furthermore, assembling nanostructures and following the carbon nanotube are carried out by using SAFLP. These experiments indicate that accurate positioning tip in AFM-based observation and manipulation can provide valid nanomanipulation in N/MEMS assembly, and the following nano-objects such as nanotube in real-time observation, which will promote automation implementation in nanomanipulation.

Many small insects such as water striders can leap from water surface. Inspired by their jumping capability, we present the design of a novel, miniature, water surface jumping robot in this paper. Jumping from water surface is more challenging than jumping from ground due to the liquid water surface. We address this problem by using carbon fiber strip to store energy, two wings to flap the water surface, a hollow body to initially support the robot, and an intermittent gear train to charge and release energy. With such a design, the final robot weighs around 12.5 g and has a maximum size of 10 cm. Experimental results show that the robot can jump up to 9.5 cm in height, which is close to the predicted results from a dynamic model developed by us to capture the hydrodynamic behaviors of the robot during the whole jumping process. The research presented in this paper offers a new design of tiny robots for mimicking the water-jumping capability of aquatic insects. The robot, if equipped with sensors, can be employed for aquatic environmental monitoring of water quality.

Scanning probe microscopy (SPM) technology plays the irreplaceable role in investigating micro/nano world, which has been bringing tremendous development opportunities to various fields. To enhance maneuverability, SPM can be modified into a nanomanipulation system with its scanning probe as the end-effector. The probe is commonly mounted on smart material based actuators to generate precise motion with nanometer level resolution. However, instinctive hysteretic characteristics ubiquitously exist in smart material actuators, which degrade their arbitrary positioning precision. To effectively represent and further reduce complex hysteretic effects, this paper proposes to utilize the modified Prandtl-Ishlinskii (PI) model: extended unparallel PI (EUPI) model, which possesses advantages such as the flexible modeling capability (compared to the prevalently implemented modified PI models) and the easy-to-use property for construction and identification (compared to the well known Preisach model and the Generalized PI (GPI) model). To effectively reduce complex hysteresis, the EUPI model based compensator (IMUPI compensator) is required to be flexible and precise. To efficiently design such a compensator satisfying stability requirement, this study proposes a systematic approach, including stabilizing gain selection and analytical calculation of boundary gains of the EUPI irreversible component. As a demonstration, satisfactorily precise IMUPI compensator was established according to this systematic design approach and tested through simulations on rectifying Atomic Force Microscopy (AFM, one special SPM) imaging process distorted by complex hysteresis.

The coming era of personalized cancer treatment is presenting automation with unprecedented opportunities. Currently, the drug susceptibility test of clinical cancer patients is mainly dependent on manual labor with a low level of automation. Automating the process of primary cancer cell detection will potentially have tremendous economic benefits and social significance. Automated cancer cell detection means developing robotic and automation equipments to handle single cells and molecules at the micro/nanometer-scale. The achievements of information science, engineering technology, life sciences, and nanotechnology in the past decades have led to the birth of robots that can perform effective manipulations on single living cells at the micro/nanometer-scale in aqueous conditions, opening the door to automated cancer cell detection. However, there is still a huge gap between current single-cell micro/nano automation technology and clinical requirements for personalized medicine. In this paper, we will review the progress of single-cell micro/nano automation technology in recent years and discuss the facing challenges and future directions in three aspects, including automated cell isolation and delivery, automatically acquiring the physiological features of cells and data analysis.

Inspired by the aerial maneuvering ability of lizards, we present the design and control of MSU (Michigan State University) tailbot—a miniature-tailed jumping robot. The robot can not only wheel on the ground, but also jump up to overcome obstacles. Moreover, once leaping into the air, it can control its body angle using an active tail to dynamically maneuver in midair for safe landings. We derive the midair dynamics equation and design controllers, such as a sliding mode controller, to stabilize the body at desired angles. To the best of our knowledge, this is the first miniature (maximum size $7.5$ cm) and lightweight ( $26.5$ g) robot that can wheel on the ground, jump to overcome obstacles, and maneuver in midair. Furthermore, tailbot is equipped with on-board energy, sensing, control, and wireless communication capabilities, enabling tetherless or autonomous operations. The robot in this paper exemplifies the integration of mechanical design, embedded system, and advanced control methods that will inspire the next-generation agile robots mimicking their biological counterparts. Moreover, it can serve as mobile sensor platforms for wireless sensor networks with many field applications.

Quick tracking in nano-manipulation has been attracting increasing attention among scientific researchers and engineers because it can significantly enhance the effectiveness and efficiency of nano-manipulation. The main reasons that hinder the improvement of accuracy and efficiency of nano-manipulation are the lack of effective real-time tracking and unavoidable perturbations by uncertainties and nonlinearities in the manipulation system. In this paper, we present a new strategy based on compressive sensing to realize quick real-time tracking nano-manipulation trajectory, and build a new kinematic model for objects to be manipulated to overcome the effect of tip positioning and contacting biases on nano-manipulation with AFM. With this approach, the deviation of the object from the predesigned trajectory during the manipulation can be corrected with up to two-thirds of time less than the traditional method, and the object can be smoothly moved to any destination in the nano-space. The approach requires no priori knowledge about the system, environment, and objects being manipulated. It is validated that this strategy works for both hard regular objects and soft irregular samples by experiments.

China has had the largest market for industrial robots in the world since 2013. With market needs and governmental support, the Chinese robot industry is expanding at an unprecedented rate in order to meet the challenges and opportunities of the rapidly developing Chinese economy. In this paper, the current state of the Chinese robot market and industry is summarised. Strategies for developing the Chinese robot industry are further discussed. It has been widely realised that the major obstacle in developing Chinese industrial robots has been the lack of capability to produce high-quality robot components such as motor drives, gearboxes, and controllers. Over the past 30 years, significant investments from the government and private sectors have been made in order to tackle this problem. However, the Chinese robot industry still faces major difficulties today. In the design and manufacturing of these components, “know-how” plays an important role. It is essential to obtain such know-how in order to overcom...

Atomic force microscopy (AFM) is originally used to observe the sample surface, and then extended to the area of nano-manipulation. It can be quite valuable in the further study of maneuvering nano-particles. Because of the influence of the tip morphology on the tip pushing direction, it is difficult to establish an effective operating model for stably manipulating nanoparticles with controllable manipulation results. To resolve this problem, the acting force of manipulating the nano-particle is analyzed firstly based on the least action principle. Then the influence of the contact point between the nano-particle and the tip is taken into account on the pushing direction, and manipulation of the nano-particle is modeled to predict its position after manipulation. Next, the model parameter is calibrated through several tests. Finally, the proposed model is verified by assembling the nano-structure. The experimental results illustrate that the model can effectively predict the nano-particle position after maneuvering, and can improve the manipulation efficiency.

Bio-syncretic robots, consisting of living biological materials and traditional electromechanical systems, have attracted lots of attention due to the potentialities of self-sensing, self-actuation and self-repairing with intrinsic safety and high energy conversion efficiency. However, most of current researches focus on the movement of the devices, and have ignored the study on the control of actuation unit “cells”, which is as important as motors for traditional electromechanical robots. In this work, the effects of cell culturing time, seeding concentration and functional drugs (cytochalasin and adrenalin) on contractile frequency and force strength of cardiomyocytes have been studied using scanning ion conductance microscope (SICM) and arrays of micro-pillars made of PDMS. This work will lay the foundation for the further study of quantitatively control of bio-syncretic robots actuated by cardiomyocytes and is also meaningful for the development of cytology, medicine, and clinical science.

Extensive studies have been conducted on telerobotic operations for decades due to their widespread applications in a variety of areas. Most studies have been focused on two major issues: stability and telepresence. Few have studied the influence of the operation status of the teleoperator on the performance of telerobotic operations. As subnormal operation status of the teleoperator may result in insufficient and even incorrect operations, the quality of teleoperator (QoT) is an important impact on the performance of the telerobotic operations in terms of the efficiency and safety even if both the stability and telepresence are guaranteed. Therefore, this paper investigates the online identification of the QoT and its application to telerobotic operations. The QoT is identified based on five QoT indicators which are generated based on the teleoperator’s brain EEG signals. A QoT adaptive control method is designed to adapt the velocity and responsivity of the robotic system to the operation status of the teleoperator such that the teleoperation efficiency and safety can be enhanced. The online QoT identification method was conducted on various teleoperators and the QoT adaptive control method was implemented on a mobile manipulator teleoperation system. The experimental results demonstrated the effectiveness and advantages of the proposed methods.

An application of an energy saving device for air compressor in intelligent industrial park is introduced in this paper. The program of air compressor energy saving system, working principle, and technical features are described in details. Actual running result shows that the air compressor device can greatly improve the power quality of enterprise, enhance the power factor. This device plays a role of energy saver in manufacturing process, indicates the direction of technical innovation in intelligent power for industrial park, and provides reliable technical support.

Though the structured light measurement system has been successfully applied to the profi le measurement of diffuse ob- jects, it is still a challenge to measure shiny objects due to the mix of both specular and diffuse reflections. To this end, we propose a robust encoding and decoding method in this paper. First, the monochromatic stripe patterns are utilized to eliminate the effect of texture and color of objects. Second, an intensity mask, dynam- ically adjusting the intensity of a projected pattern, is applied to avoid overexposure without any pre-knowledge of the workpiece. Thus, it is more flexible and efficient, compared with the existing methods. Third, to solve the internal reflection of the shiny part, an extrapolation model, combined with the intensity mask, is de- veloped to detect the stripe edge for pattern decoding, resulting in accurate and robust3Dreconstruction. Comparedwith traditional polarization based methods, it does not need to readjust for a new part. The experimental results show that the proposed method is capable of measuring various parts without surface pretreatment. Note to Practitioners—In the manufacturing industry, there is a demand to measure workpiece for quality control. A Coordi- nate Measurement Machine (CMM) is usually used. However, its pointwise measurement makes the inspection time consuming and cannotdo100%inspectionforalltheparts.Vision-based3Drecon- struction method could measure the parts quickly. But the method isweakagainstopticallychallengingobjects.Tothisend,thispaper proposed a robust surface coding method to measure the optically challenging object via a vision-based method.

In recent years, with the gradual depletion of traditional energy, as renewable energy representatives, new energy has developed rapidly. We know that distributed photovoltaic power generation with clean, pollution-free, easy installation, and therefore has been rapid development. However, the large number of distributed photovoltaic power generation connected to the distribution network would have a negative impact on the grid with a safe and reliable operation because of its randomness and volatility intrinsic properties. In this paper, in terms of power flow, voltage distribution, load characteristics, power quality, system protection and reliability departure, through MATLAB simulation analysis, the distribution network transformation strategies of primary and secondary devices has been proposed. It laid an important foundation for renewable energy development and the Third Industrial Revolution.

This paper introduces a kind of low-voltage dynamic reactive power compensation technology which is applied in intelligent industrial park. The system scheme, working principle, technical feature of the DCS-KB-2100 type low voltage power dynamic compensation device is recommended. According to the application result, the low voltage reactive power compensation technology has been greatly improved power quality, improve the power factor of the power grid. The advancement and stability of the low voltage reactive power dynamic compensation technology is verified. In the process of enterprise production, it gives full play to the role of energy saving and consumption reducing, points out the direction on the technological innovation of the industrial park electricity intellectualization, and provides a reliable technical support.

Conventional scanning probe microscopy (SPM)-based nanomanipulations always have to face scanner accuracy problems such as hysteresis, nonlinearity, and thermal drift. Although some scanners consist of internal position sensors, the sensitivity is not high enough to monitor high-resolution nanomanipulations. Additionally, once the scan size decreases to a nanolevel such as less than 100 nm, the noise brought by sensors is large enough to affect the performance of the closed-loop motion control system. In this paper, a non-vector space control strategy based on compressive feedback is proposed in order to improve the accuracy of SPM-based nanomanipulations. In this approach, local images (or compressive data) are used as both the reference input and feedback for a non-vector space closed-loop controller which considers the local image (or compressive data) as a set. The controller is designed in non-vector space, and it requires no prior information on features or landmarks which are widely used in traditional visual servoing. In this paper, the atomic force microscopy is used as an example of SPM to implement the non-vector space control strategy for nanomanipulations. The motivation of designing such a non-vector space controller is to solve the accuracy problem in nanomanipulation. Without this technique, the SPM-based nanomanipulations, such as nanomeasurement and nanosurgery, are difficult to conduct, with accuracy controlled under several nanometers. In order to illustrate the contributions and potential applications of this non-vector controller, at the end of this paper, an application of carbon nanotube local electrical property characterization based on a non-vector space motion control is shown to clearly verify the concept. Compared with other research in the local electrical property characterization, the non-vector space controller can ensure that the measurement accuracy (position error) is controlled within a few nanometers, which also ensures the reliability of measurement results. Additionally, this non-vector space control method can be implemented into any kind of SPM to realize a real-time control for nanomanipulation such as nanofabrication and nanoassembly.

Smart industrial park energy efficiency management system is used for solving the demanded side electric power management problem mainly in terms of scientific management. In this system, the data of electric power, electric power quality, and electric energy is acquired in real time by installing an electric power management monitor in the main load points, so as to analyze electric energy efficiency and energy consumption. A large amount of data can be obtained from the system, and if these huge amounts of data are of a value can be further analyzed, finding the unknown factors affecting enterprises energy consumption, equipment performance, and operational efficiency, and the disadvantages of the traditional data processing method. Therefore, an advanced data analysis and processing tool (i.e. efficiency data mining technology) is introduced for analyzing and mining large amounts of data monitored with the smart industrial park system.

The ability to jump is found widely among small animals such as frogs, grasshoppers, and fleas. They jump to overcome large obstacles relative to their small sizes. Inspired by the animals' jumping capability, a miniature jumping robot-Michigan State University (MSU) Jumper-has been developed. In this paper, the mechanical design, fabrication, and experimentation of the MSU jumper are presented. The robot can achieve the following three performances simultaneously, which distinguish it from the other existing jumping robots. First, it can perform continuous steerable jumping that is based on the self-righting and the steering capabilities. Second, the robot only requires a single actuator to perform all the functions. Third, the robot has a light weight (23.5 g) to reduce the damage that results from the impact of landing. Experimental results show that, with a 75° take-off angle, the robot can jump up to 87 cm in vertical height and 90 cm in horizontal distance. The robot has a wide range of applications such as sensor/communication networks, search and rescue, surveillance, and environmental monitoring.

With such advantages as nonphysical cell contact and a relatively high efficiency, the application of optical tweezers for the manipulation of biological cells has received increasing attention in recent years. The use of optical tweezers to transfer cells to user-defined goal positions is useful in many biomedical applications. In this paper, we investigate how to automatically transport biological cells using robotically controlled optical tweezers. We characterize the forces applied to a trapped cell by a dynamic viscous drag force method, which provides us insight into information on optimal motion parameters. To prevent the cell from escaping the optical trap and to ensure high efficiency in cell movement, a proportional-integral (PI) scheme, designed based on calibrated dynamic parameters, is used to determine the ideal movement velocity of the cell. The PI scheme utilizes a feedback of the actual cell displacement from the laser focus. Finally, a modified A* algorithm is adopted for path planning during automated cell transportation. Experiments are finally performed to verify the proposed approach.

For an unknown environment, how to make a mobile robot identify a target object and locate it autonomously, this is a very challenging question. In this paper, a novel multi-sensor fusion method based on a camera and a laser range finder (LRF) for mobile manipulations is proposed. Although a camera can acquire large quantities of information, it does not directly get the 3D data of the environment. Moreover, the camera image processing is complex and easily influenced from the change in ambient light. In view of the ability of the LRF to directly get the 3D coordinates of the environment and its stability against outside influence, and the superiority of the camera to acquire rich color information, the combination of the two sensors by making use of their advantages is employed to obtain more accurate measurement as well as to simplify information processing. To overlay the camera image with the measurement point cloud of the pitching LRF and to reconstruct the 3D image which includes pixel depth information, the homogeneous transformation model of the system is built. Then, based on the combination of the color features from the camera image and the shape features from the LRF measurement data, the autonomous identification and location of target object are achieved. In order to extract the shape features of the object, a two-step method is introduced, and a sliced point cloud algorithm is proposed for the preliminary classification of the measurement data of the LRF. The effectiveness of the proposed method is validated by the experimental testing and analysis carried out on the mobile manipulator platform. The experimental results show that by this method, the robot can not only identify target object autonomously, but also determine whether it can be operated, and acquire a proper grasping location.

Small part assembly has been received more and more attention recently. It is very challenging to automate small part assembly processes because of the part positioning problems, part mating related issues, and part manipulability problems etc. To facilitate the small part assembly processes, dual-arm robots have been developed. They have the advantages of flexibility and collaboration and can be used for small part assembly. In this paper we propose a small part assembly system using a dual-arm robot. In order to identify the part location, vision systems are deployed. The vision system calibration process is described. The small part assembly process is analyzed. An experimental system is constructed and experiments were performed. The experimental results demonstrate the effectiveness of our proposed system.

Industrial robot path planning for polishing is crucial to improve product quality. Current methods have many disadvantages: a) product quality is not consistent caused by the variations of part dimension, geometry and robot path accuracy; b) robot path planning is very challenging and time consuming. To solve these problems, we propose a polishing path planning method which is easy to use. A complex part is partitioned into simple surfaces first such as relatively flat surface and curved surface. The path generation for individual surface is then discussed. Because a complex part consists of several surfaces, a path connection method is also proposed to generate a whole path for a complex part. Experiments were performed to validate the proposed methods. The proposed path planning method is easy to implement and can greatly save the time for polishing path planning, thus reduce manufacturing cost.

Nanorobot has the potential to automate the manipulation and observation processes at molecular scale. Current drug discovery process is labor and cost intensive. Thus, a strong demand exists to automate this process. Here, we developed an Atomic Force Microscopy (AFM) based nanorobot for in situ sensing molecular interactions for drug discovery. The AFM tip and sample substrate are functionalized by the molecules of interest. Via measuring the interactive binding forces between these two molecules using the AFM based nanorobot, we are able to test the effectiveness of drug candidates on attenuating or enhancing the molecular interactions involved in cell signaling pathways. To measure the single molecular interactions precisely, we developed a new substrate coating method. The new method functionalizes the substrate much more evenly compared with the previous method. We further optimized settings during measuring the interactive binding force, such as coating with bovine serum albumin (BSA) and the level of indentation of AFM tip onto the substrate. With these progresses, this nanorobot measures single molecular interactions automated. We further used this nanorobot to test a small peptide, which was designed to attenuate the interactive binding force between focal adhesion kinase (FAK) and protein kinase B (AKT), two molecules involved in cell adhesion.

Cellular mechanical properties as the main physical performance characteristics have been actively studied in the past years for the study of cytobiology and the development of medicine. In this study, by combining Hertz model, a novel strategy is proposed to simultaneously measure the cellular mechanical properties including cellular mass, elasticity and viscosity, based on the principle of forced vibration stimulated by simple harmonic force, with piezoelectric transducer (PZT) as vibrator and Atomic Force Microscope (AFM) as detector. The corresponding theoretical model was derived and the simulation was realized based on the proposed model. The experiments of indentations and vibrations with myoblasts and myotubes were implemented to calculate the three mechanical parameters of cells according to the proposed strategy. The results validated the proposed approach. This work would be useful for the development of cytology, medicine, previously diagnose, specific therapy and so on.

A multi-layer coating enabled drug delivery method has been developed here to augment AFM based nanorobot technology. Being developed for over a decade, the AFM based nanorobot has been established as a key concept of nanorobotics, and has been applied in nanomaterial and biomedical related research. In these AFM based nanorobots, however, the AFM tip was mainly used as a mechanical end-effector to execute pushing and cutting in previous development. With its strong application potential in drug discovery and cell biology, AFM based nanorobots carrying functionalized end-effector are in a strong demand. Previous functionalization of AFM tip was aimed for single molecular interaction measurement. It cannot meet the high volume drug loading for localized drug delivery. Here, we developed a multi-layer coating method to load a large amount of protein on AFM tip for long-time release (∼ 40 hours). Combined with the AFM based nanorobot previously developed in our lab, this technology would enable scientists to study mechanical cellular response to protein stimulations.

Robotic systems are traditionally programmed through off-line coding interfaces for manufacturing tasks. These programming methods are usually time-consuming and cost a lot of human efforts. They cannot meet the emerging requirements of robotic systems in many areas such as intelligent manufacturing and customized production. To address this issue, this paper develops a human-friendly approach to on-site program robots manufacturing tasks through human-robot interaction by natural language without need of off-line training data. The new programming approach consists of three processes: human teaching, robot learning and robot execution. Through them, the humans are able to use natural language to on-site program robot manufacturing tasks which can involve operations of both single and groups of objects. The effectiveness of the proposed approach is illustrated through experimental results.

Though the 3-D sensing technique has achieved many successes in various applications, it is still a challenge for commercialized sensors to measure the 3-D shape of a transparent, mirror-like reflection-based glass surface. The reason is that the well-known triangle-based structure lighting method is only valid for parts with diffuse reflection property. To measure the 3-D profile of a glass surface, specially an automotive windshield, a new robot-assisted back-imaging system is introduced in this paper. Using the mirror property of the glass, encoded patterns are projected from an LCD monitor and recorded by two cameras. The distortion of structured light patterns, caused by the curvature of the glass, is used to calculate the 3-D shape. Different from the traditional structured light methods, the back-imaging system can simultaneously calculate both the coordinates and normal of the surface, which is particularly required by the glass industry. Furthermore, this paper also introduces a robot planning/control system that integrates the measurement constraints, vision model of the new back-imaging sensor, and the computer-aided design model together to automatically move the back-imaging sensor for 3-D shape measurement. The proposed methods have been implemented, and the sensor is installed on an ABB robot for measuring an automotive side-door glass. Experimental results are reported and analyzed.

A vehicle with four powered caster wheels can provide much more motion flexibility in a constrained environment. However, the dynamic modelling and control of such system is challenging due to its high redundancy. This paper investigates the dynamic model and tracking control for a four-powered-caster vehicle (4-PCV) on complex terrain without any additional sensor. The torques applied to the wheels are dynamically redistributed based on the real-time conditions of the whole wheel–ground interactions so that the vehicle can track the desired trajectory when moving on different terrains. A dynamic model considering the wheel–ground interaction is first derived. Then a novel approach based on a probability scheme is proposed to identify the status of the vehicle and the wheel slip ratio by only observing the velocity feedback from motors encoders. Based on this real-time perception information, a tracking controller and a torque distribution scheme are applied to make sure that each wheel can be self-adapted to meet a complex wheel–ground condition to eliminate or reduce the probability of slippage. The effectiveness of the proposed estimation approach and the performance of the torque distribution schemes are verified by simulation.

A special humanoid neck with low motion noise requirements yields a cable-driven parallel mechanism to imitate the rotational motion of a human neck. The fixed base and moving platform of the mechanism are connected by four cables and a column compression spring. The four cables are actuated separately, while the spring can support weight on the moving platform. Although similar mechanisms exist in the literature, the analysis of them is scarce because a flexible spring instead of a rigid kinematic chain is used as the spine. With the spring’s lateral buckling motion, a new approach must be adopted to solve the kinematics. In this paper, we propose a method that combines the kinematics with the statics to solve them simultaneously. The configuration of the moving platform is parameterized with four parameters, one of which is considered as parasitic motion. Using the spring’s lateral buckling equation, we can obtain the parasitic motion and solve the inverse position problem. The optimal design f...

This paper presents our recently developed humanoid neck system that can effectively mimic motion of human neck with very low motion noises. The features of low motion noises allows our system to work like a real human neck. Thus the level of acoustic noises from wearable equipments, such as donning respirators or chemical-resistant jackets, induced by human head motion can be simulated and investigated using such a system. Our low motion-noise humanoid head/neck system is based on the spring structure, which can generate 1 degree of freedom (DOF) jaw movement and 3DOF neck movement. To guarantee the low-noise feature, no noise-makers like gear and electro-driven parts are embedded in the head/neck structure. Instead, the motion is driven by seven polyester cables, and the actuators pulling the cables are sealed in a sound insulation box. Furthermore, statics analysis and motion control design of the system have been presented. Experimental results clearly show that the head/neck system can greatly mimic the motion of human head with an A-weighted noise level of 30 dB or below.

PurposeThe industrial robot has high repeatability but low accuracy. With the industrial robot being widely used in complicated tasks, e.g. arc welding, offline programming and surgery, accuracy of the robot is more and more important. Robot calibration is an efficient way to improve the accuracy. Previous methods such as using coordinate measurement machines, laser trackers or cameras are limited by the cost, complex operation or the resolution. The purpose of this paper is to propose an approach and calibration equipment to address these issues.Design/methodology/approachThe proposed method relies mainly upon a laser pointer attached on the end‐effector and single position‐sensitive devices (PSD) arbitrarily located on the workcell. The automated calibration procedure (about three minutes) involves aiming the laser lines loaded by the robot towards the center of the PSD surface from various robot positions and orientations. The localization is guaranteed by precise PSD feedback servoing control, which means physically the intersections of each pair of laser lines (virtual lines) are on the same point. Based on the untouched single‐point constraint, the robot joint offset calibration is implemented. Using the authors' proposed approach, a portable, low‐cost, battery‐powered, wireless and automated calibration system was implemented. Error analysis was conducted on the system.FindingsThe localization error of the developed calibration system is within 2 μm. The errors in joint space are magnified in PSD plane, and consequently the resolution in the joint space is improved. The standard deviation of the identified parameters was small (10‐2), indicating the stability of the calibration method. Both simulation and experimental results verify the feasibility of the proposed method and demonstrate the developed calibration system can identify joint offset with uncalibrated laser tool parameters.Originality/valueThe paper shows how a portable calibration system for joint offset of industrial robots was developed and how the goal of fast, automated, low‐cost, portable, and high precision calibration methods for joint offset was achieved.

Nanomanipulation with Atomic Force Microscopy (AFM) is one of the fundamental tools for nano-manufacturing. The motion control of the nanomanipulation system requires accurate feedback from the piezoelectric actuator and high frequency response from the control system. Since normal AFM control system for scanning motion is not suitable for controller of arbitrary motion, we therefore modified the hardware configuration to meet the demand of nanomanipulation control. By identifying the necessary parameters using system identification methods, we built up a new dynamic model for the modified configuration. Based on the new model and configuration, we designed and implemented a control scheme as motion controller for AFM nanomanipulation operation. The aims are to analyze various factors in the control of the AFM based nanomanipulation system. By integrating the original AFM controller with the external Linux real-time controller, we achieved a stable system with high frequency response. Several problems have been addressed based on the new control scheme, such as high frequency response, robust feedback control and non-linearity, etc. Finally this Multiple Input Single Output (MISO) system is validated by real-time nanomanipulation task. It is proved to be an effective and efficient tool for the controlling of the nanobiomanipulation operation by cutting the intercellular junction of human keratinocytes.

The main problem of Atomic Force Microscope (AFM) based nanomanipulation is the lack of real-time visual feedback. Although the model based visual feedback can partly solve this problem, the incorrect display caused by the uncertainties in the nano-environment often leads to a failed nanomanipulation. In this paper, a general strategy with three-level structure is proposed to overcome this problem. With this three-level strategy, the incorrect display can be not only real-time detected, but also on-line corrected. The difficulty to implement this strategy is that there is no continuous way to describe and model the system since both discrete and continuous commands are involved. A Petri-net based method is proposed to organize this strategy such that task scheduling, which usually deals with discrete events, as well as task planning, which usually deals with continuous events can be treated in a unified framework. This Petri-net organized strategy provides general instructions to AFM based manipulation for displaying a visual feedback which can be as close as possible to the true environment. The experimental results presented in the paper demonstrate the advantage of the proposed strategy. It also shows the increased efficiency of the AFM based nanomanipulation.

We present our development of a supermedia interface for telediagnostics of breast pathology via the Internet. Supermedia is the incorporation of multiple media and data streams, such as audio, video, ultrasound images, and tactile and haptic sensor data for enhanced telepresence capabilities. Our supermedia interface comprises an anthropomorphic arm/hand equipped with haptic and tactile sensing, ultrasound imaging capabilities, a physician interface capable of rendering both haptic and tactile information, and two-way audio and video. The supermedia interface was tested via the Internet and enables telediagnostics. Preliminary experiments with silicone breast models have demonstrated the e fectiveness of the supermedia interface for telediagnostics. The interface is expected to enhance and improve the diagnostic performance of breast pathology as well as promote telediagnostics in remote areas and for patients with cultural barriers.

A feedback-based area sensor planning system is introduced in this paper. This system is developed for automated 3D shape inspection. A CAD-guided area sensor planning system had been developed previously. However, physical properties of a part surface are usually difficult be modeled for an area sensor. Shadows, reflections, and image quality are three problems related to surface measurement quality, which cannot be predicted from a CAD model. Feedback from a measured 3D point cloud can be used for dealing with those problems by adding more viewpoints in iterations. In feedback mode, the inspection system generates viewpoints according to point clouds measured in each step. The loop stops when the obtained point clouds satisfy the measurement quality requirements. In this paper, a general framework of such area sensor planning system is introduced. The developed feedback system has been implemented for a robot-aided dimensional inspection system.

A novel mechanism for power transmission line inspection robot is presented according to the requirements of inspection tasks and characteristics of obstacles on power lines. Its configuration is introduced, and the kinematics equations and statics model are established. Then, the motion sequences for crossing the strain clamp are planned. Furthermore, the simulation of the navigation of the strain clamp has been carried out. The simulation results demonstrate that the mechanism has such characteristics as good motion stability, strong loading capacity and excellent obstacle negotiation capability.

Calibration plays an important role in industrial robots. Traditional ways are time consuming and also involve a lot of human efforts. We have proposed a dual-PSD (Position Sensitive Device) method to automatically accomplish the calibration in several minutes. The alignment control problem is the major issue in the calibration process, which requires to move a laser pointer mounted on the robot's end-effector to shoot the laser beam at one PSD center and reflect to another PSD center. This paper proposes an adaptive control method to solve the alignment problem. It can online estimate the unknown parameters between the robot base frame and the PSD frame, which are usually required before the alignment control. The advantage of the approach is that we do not need to calculate or estimate these parameters before the alignment control so it can further facilitate the automated calibration process. The effectiveness and advantages of the method is demonstrated through simulation results.

This paper presents a method of modelling and control of servomotor for safe robots. Safety has indeed come to represent one of the major themes in robotics research for those applications that bring robots in contact with humans. Beyond this is the classical research topic of impedance control which has recently found new interest after the progress in the improved control and sensing principles. There exist a few different strategies for robot impedance control, where different amounts of sensor information are used. Among them, a kind of sensorless force control, torque observer method based on motor model, current and position information has many advantages and is widely researched. This paper discusses the permanent magnet synchronous motor (PMSM) modelling and control for the sensorless force control of safe robots. DSP controller for performing the vector and current control functions for a PMSM is implemented, and field oriented control is used to convert the PMSM into equivalent separately excited dc machines which have highly desirable control characteristics. Also, the nonlinear equations of the PMSM, PID controller equations and a real time model of the inverter switches are used in the simulation. At last, key theoretical results are verified by loading experiments.

For mobile robot local path planning under outdoor environment, Ridge Regression Extreme Learning Machines (RRELM) is adopted, it is a fast machine learning classification method to apply in path planning. Firstly, the laser rangefinder data are extracted and marked to describe the outdoor environment. Secondly, ridge regression theory is utilized to improve the generalization ability of ELM for local path planning. Meanwhile, the start-goal point constraint is considered for planning. Additionally, abrupt dynamic obstacle is regarded as a kind of disturbance to plan the path by RRELM. Then the optimal path is estimated by the distance evaluation function among feasible paths. Finally, a great deal of outdoor robot simulation experiments are shown that RRELM find out the safety path for outdoor robot, and the generalization ability, smoothness and rapidity of RRELM for path planning are better than SVM and ELM, furthermore, the performance of RRELM for the dynamic environment is also efficient.

Control and actuation are the most important factors that determine the performance of traditional electromechanical robots. Bio-syncretic actuators are a potential trend for the next generation of robots to overcome the challenges in the control and actuation faced by the traditional robots and many novel bio-syncretic actuators have been reported with various biological entities. However, none of these works considers the movement control of such bio-syncretic robots. In this paper, we propose a new actuation approach strategy to assist bio-actuation with remote magnetic field, and present a dolphin-shaped micro-swimmer. Cardiomyocytes are used for bio-actuation. The mathematical model for the micro-swimmer is developed and is validated by comparing the experimental result and simulation result based on the properties of beating cells measured by SICM and AFM. This work is fundamental to the development of bio-syncretic robots.

Small insects can use vision to successfully land on arbitrary surfaces. For miniature robots with a size of a few centimeters, it is challenging to achieve similar capabilities due to their small sizes. To address this problem, we present a new vision based landing algorithm using a non-vector space control method, which formulates the system dynamics in the space of sets—different from the traditional vector space with a linear structure. Using a stabilization controller in the non-vector space, we can control the landing posture of a small robot with an active tail. Preliminary experimental results demonstrate the effectiveness of the proposed approach. The research presented in this paper, together with the idea of compressive feedback—when only a compressed image is used for feedback—can potentially achieve real time onboard vision based control for miniature robots.

In this paper, two techniques have been presented for slippage detection. They are independent of sensor signal type and are promising for general use on tactile array sensors. The first method is based on frequency analysis of the correlation coefficient sequence of sensor array data sampled as time evolves. The main idea is that a slippage causes heavier fluctuation in the sensor signal distribution and values than a static case. The second approach employs 2-D cross correlation to detect displacements of the sliding object from tactile images, which makes it possible to estimate the slippage velocity using commercially available sensors rather than custom hardware. Experiments have been implemented to evaluate the proposed approaches. It can be seen that the first method is capable of detecting both translational and rotational slippage. Also, it works well in dynamic environments. Additionally, the ability of the second method to detect slippage velocity has been confirmed in the experiment.

Calibration is crucially important for the accuracy of industrial robots. Traditional calibration methods for joint offsets usually required a complicated setup and considerable expenditures. We have proposed a dual-PSD (Position Sensitive Device) based industrial robot calibration system to calibrate the industrial robot in minutes. The laser alignment formulated as a multi-objective position control problem is a fundamental issue for the system. It requires controlling a laser beam to shoot at the center of one PSD and meanwhile controlling its reflected laser beam to shoot at the center of another PSD. This paper investigates the modeling of this problem and proposes a simultaneous control approach to perform the multi-objective position control. The effectiveness of the designed method is illustrated through simulation and experimental results.

Calibration plays a critically important role for improving the accuracy of industrial robots. Recently, position sensitive device (PSD) based calibration methods provide a more efficient way to perform joint offset calibration than the conventionally used methods. We have proposed a dual-PSD based method to accurately calibrate the joint offsets of industrial robots. However, the required alignment of laser beam to shoot at the two PSD centers was performed separately, which required to pre-know some parameters for the alignment task. This paper proposes a simultaneous laser beam alignment method without knowing these parameters to perform the laser beam alignment task. The modeling and control for the alignment system are derived and simulation results illustrate the effectiveness of the proposed methods.

In our prior work [1], a concept of QoT was proposed to represent the confidence of the decisions and commands generated by the teleoperator. It reflected the operation status of the teleoperator. The investigation proved that the QoT varied over different times of a day due to the fatigue level. However, it did not consider the variation of the QoT during the same time period. In fact, the QoT of these teleoperators changed as they repeated the same task a few times. One main reason was because the QoT was also influenced by the training of the teleoperator. This paper investigated the effect of the training on the QoT. A B-Spline neural network based method was used to identify the QoT variation due to different training level online. Three experiment results were provided to investigate the influence of training on the QoT. The results were obtained in the end.

Atomic force microscopy (AFM) is a powerful measurement instrument, which has been widely implemented in various fields. To enhance the maneuverability, an AFM can be modified and its cantilever can be controlled as a robotic end-effector. To precisely control the nanorobots, their scanners inherent hysteresis, which is the main disadvantage, should be compensated sufficiently. Mostly, hysteresis compensators used in AFM control system only employ the symmetric models, which cannot well represent the asymmetric hysteresis phenomena of piezo-scanners. However, under many cases, the smart material based scanners possess asymmetric hysteresis slightly or seriously, which is far more complex than the regular symmetric case; in addition, for commercial or customized AFMs, the scanners are usually controlled without feedback. These drawbacks tackle further improvement of positioning accuracy of AFM systems. To effectively describe and further reduce the hysteresis of general cases, we propose a new type of generalized Prandtl-Ishlinskii (PI) operator based superposition model, named unparallel PI (UPI) model. The flexible edge of the UPI operator can be tilted freely within a defined range, which enables it to capture asymmetric hysteresis efficiently. To cancel the hysteresis effect in an open-loop system, three inverse compensation approaches are proposed, compared, and the corresponding stability is analyzed. Experiments with AFM based nanorobot verified the proposed approaches with convincing performance.

Automatic trajectory generation for spray painting is highly desirable for today’s automotive manufacturing. Generating paint gun trajectories for free-form surfaces to satisfy paint thickness requirements is still highly challenging due to the complex geometry of free-form surfaces. In this paper, a CAD-guided paint gun trajectory generation system for free-form surfaces has been developed. The system utilizes the CAD information of a free-form surface and a paint gun model to automatically generate a paint gun trajectory to satisfy the paint thickness requirements. Complex surfaces are divided into patches to satisfy the constraints. A trajectory integration algorithm is developed to integrate the trajectories of the patches. The paint thickness deviation from the required paint thickness is optimized by modifying the paint gun velocity. A paint thickness verification method is also developed to verify the generated trajectories. The results of simulations have shown that the trajectory generation system achieves satisfactory performance. This trajectory generation system can also be applied to generate trajectories for many other CAD-guided robot trajectory planning applications in surface manufacturing.

Purpose – Aims to demonstrate how an automated robot program generation method can be developed and implemented.Design/methodology/approach – A visual and force servoing method to automatically generate robot paths and robot programs, based on position, force and vision sensor fusion, was developed.Findings – By using a hybrid control algorithm the robot is controlled to follow the feature on a surface with position and orientation control.Originality/value – The developed method can be applied to generate tool paths for many manufacturing tasks automatically, which can greatly reduce the robot programming time and decrease the manufacturing cost.