Tricycle-style operation interface for children to control a telepresence robot

Telepresence robots will provide significant value to childhood education. They will offer children opportunities to join remote classrooms and to communicate with speakers of different languages in more enriched ways than are available by conventional video conferencing. However, the introduction of child-operated telepresence robots has yet to be tested. The design of the operation interface presents a particular challenge. In this study, we report the development of a tricycle-style operation interface based on requirements identified through classroom field observations. It was designed for intuitive use, even by young children, without the need of detailed instruction. The usability of the interface was tested in a field experiment involving 20 participants (4–8 years old). The participants were asked to perform six elementary tasks using a telepresence robot system controlled either by the tricycle-style interface or a standard video-game controller. The operational performance of the tricycle-style interface was found to be superior to that of the standard controller. The advantages and disadvantages of both interfaces are discussed.     

Symmetry position/force hybrid control for cooperative object transportation using multiple humanoid robots

A symmetry position/force hybrid control framework for cooperative object transportation tasks with multiple humanoid robots is proposed in this paper. In a leader-follower type cooperation, follower robots plan their biped gaits based on the forces generated at their hands after a leader robot moves. Therefore, if the leader robot moves fast (rapidly pulls or pushes the carried object), some of the follower humanoid robots may lose their balance and fall down. The symmetry type cooperation discussed in this paper solves this problem because it enables all humanoid robots to move synchronously. The proposed framework is verified by dynamic simulations.     

Modeling and design of a humanoid robotic face based on an active drive points model

This study develops a face robot with human-like appearance for making facial expressions similar to a specific subject. First, an active drive points (ADPs) model is proposed for establishing a robotic face with less active degree of freedom for bipedal humanoid robots. Then, a robotic face design method is proposed, with the robot possessing similar facial appearance and expressions to that of a human subject. A similarity evaluation method is presented to evaluate the similarity of facial expressions between a robot and a specific human subject. Finally, the proposed facial model and the design methods are verified and implemented on a humanoid robot platform.     

Knee rehabilitation using an intelligent robotic system

There is an increasing trend in using robots for medical purposes. One specific area is the rehabilitation. There are some commercial exercise machines used for rehabilitation purposes. However, these machines have limited use because of their insufficient motion freedom. In addition, these types of machines are not actively controlled and therefore can not accommodate complicated exercises required during rehabilitation. In this study, a rule based intelligent control methodology is proposed to imitate the faculties of an experienced physiotherapist. These involve interpretation of patient reactions, storing the information received, acting according to the available data, and learning from the previous experiences. Robot manipulator is driven by a servo motor and controlled by a computer using force/torque and position sensor information. Impedance control technique is selected for the force control.     

Detection and tracking for robotic visual servoing systems

Robot manipulators require knowledge about their environment in order to perform their desired actions. In several robotic tasks, vision sensors play a critical role by providing the necessary quantity and quality of information regarding the robot's environment. For example, “visual servoing” algorithms may control a robot manipulator in order to track moving objects that are being imaged by a camera. Current visual servoing systems often lack the ability to detect automatically objects that appear within the camera's field of view. In this research, we present a robust “figureiground” framework for visually detecting objects of interest. An important contribution of this research is a collection of optimization schemes that allow the detection framework to operate within the real-time limits of visual servoing systems. The most significant of these schemes involves the use of “spontaneous” and “continuous” domains. The number and location of continuous domains are. allowed to change over time, adjusting to the dynamic conditions of the detection process. We have developed actual servoing systems in order to test the framework's feasibility and to demonstrate its usefulness for visually controlling a robot manipulator.     

A 3D simulator for autonomous robotic fish

This paper presents a 3D simulator used for studying the motion control and autonomous navigation of robotic fish. The simulator's system structure and computation flow are presented. Simplified kinematics and hydrodynamics models for a virtual robotic fish are proposed. Many other object models are created for water, obstacles, sonar sensors and a swimming pool. Experimental results show that the simulator provides a, realistic and convenient way to develop autonomous navigation algorithms for robotic fish.     

Crop recognition under weedy conditions based on 3D imaging for robotic weed control

A 3D time‐of‐flight camera was applied to develop a crop plant recognition system for broccoli and green bean plants under weedy conditions. The developed system overcame the previously unsolved problems caused by occluded canopy and illumination variation. An efficient noise filter was developed to remove the sparse noise points in 3D point cloud space. Both 2D and 3D features including the gradient of amplitude and depth image, surface curvature, amplitude percentile index, normal direction, and neighbor point count in 3D space were extracted and found effective for recognizing these two types of plants. Separate segmentation algorithms were developed for each of the broccoli and green bean plant in accordance with their 3D geometry and 2D amplitude characteristics. Under the experimental condition where the crops were heavily infested by various types of weed plants, detection rates over 88.3% and 91.2% were achieved for broccoli and green bean plant leaves, respectively. Additionally, the crop plants were segmented out with nearly complete shape. Moreover, the algorithms were computationally optimized, resulting in an image processing speed of over 30 frames per second.     

Design of a low-cost five-finger anthropomorphic robotic arm with nine degrees of freedom

The aim of this work was to design and demonstrate a dexterous anthropomorphic mobile robotic arm with nine degrees of freedom using readily available low-cost components to perform different object-picking tasks for immobile patients in developing nations. The robotic arm consists of a shoulder, elbow, wrist and five-finger gripper. It can perform different gripping actions, such as lateral, spherical, cylindrical and tip-holding gripping actions using a five-finger gripper; each finger has three movable links. The actuator used for the robotic arm is a high torque dc motor coupled with a gear assembly for torque amplification, and the five-finger gripper consists of five cables placed like tendons in the human arm. The robotic arm utilizes a controller at every link to trace the desired trajectory with high accuracy and precision. Digital implementation of the control algorithm is done on an Atmel Atmega-16 microcontroller using trapezoidal approximation and Newton's backward difference methods. The arm can be programmed or controlled manually to perform a variety of object-picking tasks. A prototype of the robotic arm was constructed, and test results on a variety of object-picking tasks are presented.     

Super-low friction and lightweight hydraulic cylinder using multi-directional forging magnesium alloy and its application to robotic leg

Abstract

One of the most important missions for robots is to operate in severe environments, and these situations require robots to have ‘toughness’ which can overcome large shocks, degraded communication quality, unexpected condition, and other critical accidents. Although there are many kinds of approaches to realize tough robotic systems, developing a tough actuators is one of the key technologies for them. We focus on hydraulic actuators and attempt to develop a tough robotic actuator with greater toughness than the electromagnetic actuators used in conventional robotic systems. In general, hydraulic actuators have enough toughness for severe environments, but their controllability and lightness are insufficient for robot systems. Herein, we propose novel hydraulic actuators that realizes lightweight with a multidirectional-forging magnesium alloy and have high controllability by low friction pistons. Prototypes were developed to examine the fundamental characteristics of the actuators and compare the two approaches for the low-friction pistons: one is based on a packing mechanism using an elastic restoring pressure, and the other utilizes a fluid-bearing technology. After basic experiments, the prototype was applied to a robotic leg to verify their potential in actual robotic systems. The robotic leg successfully jumped 260 mm in height with 21 MPa.     

Operational learning with sensory feedback for controlling a robotic thumb using the posterior auricular muscle

Extra robotic limbs in a robotic system that are designed to augment and expand human abilities have received attention in the field of wearable robotics. We aim to develop a robotic system that is controlled by body parts that are not used on a daily basis in order to augment and expand human abilities. This paper presents operational learning experiments for manipulating a robotic thumb using the posterior auricular muscle, a body part that is not used in everyday life. In these experiments, reaching motions were executed using sensory feedback in the robotic thumb through a device that continuously displays its position. The experimental results indicate the proposed operational learning experiments improve the ability to contract the posterior auricular muscles. In addition, the results indicate the operability of a robotic thumb could be improved by acquiring internal models through repetitive operational learning.     

A distributed control scheme for multiple robotic vehicles to make group formations

This paper presents a novel distributed control scheme of multiple robotic vehicles. Each robotic vehicle in this scheme has its own coordinate system, and it senses its relative position and orientation to others, in order to make group formations. Although there exists no supervisor and each robotic vehicle has only relative position feedback from the others in the local area around itself, all the robotic vehicles are stabilized, which we have succeeded in proving mathematically only in the cases where the attractions between the robots are symmetrical. Each robotic vehicle especially has a two-dimensional control input referred to as a “formation vector” and the formation is controllable by the vectors. The validity of this scheme is supported by computer simulations.     

Automated wall-climbing robot for concrete construction inspection

Human-made concrete structures require cutting-edge inspection tools to ensure the quality of the construction to meet the applicable building codes and to maintain the sustainability of the aging infrastructure. This paper introduces a wall-climbing robot for metric concrete inspection that can reach difficult-to-access locations with a close-up view for visual data collection and real-time flaws detection and localization. The wall-climbing robot is able to detect concrete surface flaws (i.e., cracks and spalls) and produce a defect-highlighted 3D model with extracted location clues and metric measurements. The system encompasses four modules, including a data collection module to capture RGB-D frames and inertial measurement unit data, a visual–inertial navigation system module to generate pose-coupled keyframes, a deep neural network module (namely InspectionNet) to classify each pixel into three classes (background, crack, and spall), and a semantic reconstruction module to integrate per-frame measurement into a global volumetric model with defects highlighted. We found that commercial RGB-D camera output depth is noisy with holes, and a Gussian-Bilateral filter for depth completion is introduced to inpaint the depth image. The method achieves the state-of-the-art depth completion accuracy even with large holes. Based on the semantic mesh, we introduce a coherent defect metric evaluation approach to compute the metric measurement of crack and spall area (e.g., length, width, area, and depth). Field experiments on a concrete bridge demonstrate that our wall-climbing robot is able to operate on a rough surface and can cross over shallow gaps. The robot is capable to detect and measure surface flaws under low illuminated environments and texture-less environments. Besides the robot system, we create the first publicly accessible concrete structure spalls and cracks data set that includes 820 labeled images and over 10,000 field-collected images and release it to the research community.     

网络服务质量动态监测的远程机器人控制

为了有效地控制远程机器人 ,提高机器人的运动控制精度 ,通过测量网络动态性能 ,得到了网络服务质量参数 ;通过排队网络模型求解 ,得出远程机器人在线控制参数 ;通过对远程移动机器人的控制实验 ,验证了本控制算法的可行性 .本控制算法可以推广应用于对其它网络设备的远程监控     

Distributed fuzzy discrete event system for robotic sensory information processing

Abstract: This paper presents a novel intelligent sensory information processing technique using a fuzzy discrete event system (FDES) for robotic control. The proposed method combines the predictive control approach of a discrete event system with the approximate reasoning aspect of fuzzy logic. It develops a supervisory control strategy for behavior-based robotic control using distributed FDES. The application of distributed FDES eliminates the formation of complex fuzzy predicates and a large fuzzy rule-base. The FDES-based approach also provides means for analyzing behavior-based decision-making using the observability and controllability of an FDES. The observability of an FDES describes uncertainties in sensory data, and the controllability of an FDES exploits uncertain state transitions in a dynamic environment. Comprehensive experiments on behavior-based mobile robot navigation are presented to authenticate the performance of the proposed methodology.     

Novelty detection and segmentation based on Gaussian mixture models: A case study in 3D robotic laser mapping

This article proposes a framework to detect and segment changes in robotics datasets, using 3D robotic mapping as a case study. The problem is very relevant in several application domains, not necessarily related with mobile robotics, including security, health, industry and military applications. The aim is to identify significant changes by comparing current data with previous data provided by sensors. This feature is extremely challenging because large amounts of noisy data must be processed in a feasible way. The proposed framework deals with novelty detection and segmentation in robotic maps using clusters provided by Gaussian Mixture Models (GMMs). GMMs provides a feature space that enables data compression and effective processing. Two alternative criteria to detect changes in the GMM space are compared: a greedy technique based on the Earth Mover’s Distance (EMD); and a structural matching algorithm that fulfills both absolute (global matching) and relative constraints (structural matching). The proposed framework is evaluated with real robotic datasets and compared with other methods known from literature. With this purpose, 3D mapping experiments are carried out with both simulated data and real data from a mobile robot equipped with a 3D range sensor.     

Smart robotic mobile fulfillment system with dynamic conflict-free strategies considering cyber-physical integration

Smart mobile robots are deployed to the warehouse environments to improve the efficiency, because of its characteristics of high automation and flexibility characteristics. However, the trajectory planning is a great challenge especially when a number of mobile robotics operates in the warehouse simultaneously. This paper proposes a cyber-physical system model for smart robotic warehouse to implement the workflow data collection and procedure monitor. A decoupled method is presented to find a conflict-free path for the mobile vehicles in the warehouses, after distributing destinations to mobile robots to minimize the total travel distance. The improved A* algorithm is applied to find paths from the source node to the destination node for single mobile vehicle in the domain of smart logistics. Collisions are detected by comparing the occupying time window of each mobile vehicle. Three collision avoidance strategies are developed to solve the conflicts and the candidate path with the minimal completion time is selected as the final determined route. The contribution of the paper is to propose a CPS-enabled robotic warehouse with dynamic conflict-free strategy to self-configure the path to optimize warehouse operation efficiency.     

Cooperative modalities in robotic tele-rehabilitation using nonlinear bilateral impedance control

A nonlinear model reference adaptive bilateral impedance controller is proposed that can accommodate various cooperative tele-rehabilitation modes for patient–therapist interaction using a multi-DOF tele-robotic system. In this controller, two reference impedance models are implemented for the master and slave robots using new model reference adaptive control laws for the nonlinear bilateral teleoperation system. “Hand-over-hand” and “adjustable-flexibility” are two modes of patient–therapist cooperation that are realized using the proposed strategy. The Lyapunov-based stability proof guarantees the patient’s and the therapist’s safety during the cooperation and interaction with robots, even in the presence of modeling uncertainties of the multi-DOF teleoperation system. The performance of the proposed bilateral impedance controller is experimentally investigated for upper-limb tele-rehabilitation in the two mentioned cooperation modes.     

基于三维激光引导的加料机械臂精准定位研究

在铁水加注等钢铁冶炼的重型生产场景中,由于作业行程远、温度高等原因均采用人工操作。设计开发了基于三维激光扫描技术的加料机械臂精准定位系统。该系统以机械臂和三维激光扫描仪为基础,采用手眼标定方式得到转换矩阵,根据所获得的靶球坐标得到下料口在机械臂坐标系下的精确位置,最终实现下料管的安装和拆卸。现场测试证明,该系统可以替代操作人员进行自动加料作业。     

采用遥感影像的林地建模研究

提出了一种全新的林地建模方法,对生长着树木的林地获取地面序列影像,利用影像分割实现树木信息的自动识别,通过基于地面区域约束的点云提取算法获得地面高精度密集点云,最后应用三次Beta样条曲线插值模型实现了林地等高线的建模。该方法将摄影测量技术应用于林地建模,解决了无法对有树木遮挡的地面进行建模的难题,提高了林地建模的效率。     

Reconstruction of 3D contour with an active laser‐vision robotic system

This paper presents a 3D contour reconstruction approach employing a wheeled mobile robot equipped with an active laser‐vision system. With observation from an onboard CCD camera, a laser line projector fixed‐mounted below the camera is used for detecting the bottom shape of an object while an actively‐controlled upper laser line projector is utilized for 3D contour reconstruction. The mobile robot is driven to move around the object by a visual servoing and localization technique while the 3D contour of the object is being reconstructed based on the 2D image of the projected laser line. Asymptotical convergence of the closed‐loop system has been established. The proposed algorithm also has been used experimentally with a Dr Robot X80sv mobile robot upgraded with the low‐cost active laser‐vision system, thereby demonstrating effective real‐time performance. This seemingly novel laser‐vision robotic system can be applied further in unknown environments for obstacle avoidance and guidance control tasks. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society