Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.

Dynamic Visual Servoing With Chaos Control for Redundant Robots

This paper presents a new dynamic visual control system for redundant robots with chaos compensation. In order to implement the visual servoing system, a new architecture is proposed that improves the system maintainability and traceability. Furthermore, high performance is obtained as a result of parallel execution of the different tasks that compose the architecture. The control component of the architecture implements a new visual servoing technique for resolving the redundancy at the acceleration level in order to guarantee the correct motion of both end-effector and joints. The controller generates the required torques for the tracking of image trajectories. However, in order to guarantee the applicability of this technique, a repetitive path tracked by the robot-end must produce a periodic joint motion. A chaos controller is integrated in the visual servoing system and the correct performance is observed in low and high velocities. Furthermore, a method to adjust the chaos controller is proposed and validated using a real three-link robot.

A survey of control architectures for autonomous mobile robots

MEDEIROS, Adelardo A. D.A survey of control architectures for autonomous mobile robots. J. Braz. Comp. Soc., Campinas, v. 4, n. 3, abr. 1998 .Disponível em: Acesso: 27 set. 2010.

A survey of control architectures for autonomous mobile robots

MEDEIROS, Adelardo A. D.A survey of control architectures for autonomous mobile robots. J. Braz. Comp. Soc., Campinas, v. 4, n. 3, abr. 1998 .Disponível em: Acesso: 27 set. 2010.

Genetic algorithm seeding of idiotypic networks for mobile-robot navigation

Robot-control designers have begun to exploit the properties of the human immune system in order to produce dynamic systems that can adapt to complex, varying, real-world tasks. Jerne’s idiotypic-network theory has proved the most popular artificial-immune-system (AIS) method for incorporation into behaviour-based robotics, since idiotypic selection produces highly adaptive responses. However, previous efforts have mostly focused on evolving the network connections and have often worked with a single, preengineered set of behaviours, limiting variability. This paper describes a method for encoding behaviours as a variable set of attributes, and shows that when the encoding is used with a genetic algorithm (GA), multiple sets of diverse behaviours can develop naturally and rapidly, providing much greater scope for flexible behaviour-selection. The algorithm is tested extensively with a simulated e-puck robot that navigates around a maze by tracking colour. Results show that highly successful behaviour sets can be generated within about 25 minutes, and that much greater diversity can be obtained when multiple autonomous populations are used, rather than a single one.

Inpatient facial expression recognition with SMS alert

Facial expression recognition (FER) has been dramatically developed in recent years, thanks to the advancements in related fields, especially machine learning, image processing and human recognition. Accordingly, the impact and potential usage of automatic FER have been growing in a wide range of applications, including human-computer interaction, robot control and driver state surveillance. However, to date, robust recognition of facial expressions from images and videos is still a challenging task due to the difficulty in accurately extracting the useful emotional features. These features are often represented in different forms, such as static, dynamic, point-based geometric or region-based appearance. Facial movement features, which include feature position and shape changes, are generally caused by the movements of facial elements and muscles during the course of emotional expression. The facial elements, especially key elements, will constantly change their positions when subjects are expressing emotions. As a consequence, the same feature in different images usually has different positions. In some cases, the shape of the feature may also be distorted due to the subtle facial muscle movements. Therefore, for any feature representing a certain emotion, the geometric-based position and appearance-based shape normally changes from one image to another image in image databases, as well as in videos. This kind of movement features represents a rich pool of both static and dynamic characteristics of expressions, which playa critical role for FER. The vast majority of the past work on FER does not take the dynamics of facial expressions into account. Some efforts have been made on capturing and utilizing facial movement features, and almost all of them are static based. These efforts try to adopt either geometric features of the tracked facial points, or appearance difference between holistic facial regions in consequent frames or texture and motion changes in loca- facial regions. Although achieved promising results, these approaches often require accurate location and tracking of facial points, which remains problematic.

Reactive reaching and grasping on a humanoid: Towards closing the action-perception loop on the iCub

We propose a system incorporating a tight integration between computer vision and robot control modules on a complex, high-DOF humanoid robot. Its functionality is showcased by having our iCub humanoid robot pick-up objects from a table in front of it. An important feature is that the system can avoid obstacles - other objects detected in the visual stream - while reaching for the intended target object. Our integration also allows for non-static environments, i.e. the reaching is adapted on-the-fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. Furthermore we show that this system can be used both in autonomous and tele-operation scenarios.

Robotics for the mining industry

The mining industry is highly suitable for the application of robotics and automation technology since the work is both arduous and dangerous. However, while the industry makes extensive use of mechanisation it has shown a slow uptake of automation. A major cause of this is the complexity of the task, and the limitations of existing automation technology which is predicated on a structured and time invariant working environment. Here we discuss the topic of mining automation from a robotics and computer vision perspective — as a problem in sensor based robot control, an issue which the robotics community has been studying for nearly two decades. We then describe two of our current mining automation projects to demonstrate what is possible for both open-pit and underground mining operations.

Rubbing shoulders with mobile service robots

This paper is not about the details of yet another robot control system, but rather the issues surrounding realworld robotic implementation. It is a fact that in order to realise a future where robots co-exist with people in everyday places, we have to pass through a developmental phase that involves some risk. Putting a “Keep Out, Experiment in Progress” sign on the door is no longer possible since we are now at a level of capability that requires testing over long periods of time in complex realistic environments that contain people. We all know that controlling the risk is important – a serious accident could set the field back globally – but just as important is convincing others that the risks are known and controlled. In this article, we describe our experience going down this path and we show that mobile robotics research health and safety assessment is still unexplored territory in universities and is often ignored. We hope that the article will make robotics research labs in universities around the world take note of these issues rather than operating under the radar to prevent any catastrophic accidents.

Bringing the farmer perspective to agricultural robots

The research reported in this paper explores autonomous technologies for agricultural farming application and is focused on the development of multiple-cooperative agricultural robots (AgBots). These are highly autonomous, small, lightweight, and unmanned machines that operate cooperatively (as opposed to a traditional single heavy machine) and are suited to work on broadacre land (large-scale crop operations on land parcels greater than 4,000m2). Since this is a new, and potentially disruptive technology, little is yet known about farmer attitudes towards robots, how robots might be incorporated into current farming practice, and how best to marry the capability of the robot with the work of the farmer. This paper reports preliminary insights (with a focus on farmer-robot control) gathered from field visits and contextual interviews with farmers, and contributes knowledge that will enable further work toward the design and application of agricultural robotics.

AI in locomotion: Challenges and perspectives of underactuated robots

This article discusses the issues of adaptive autonomous navigation as a challenge of artificial intelligence. We argue that, in order to enhance the dexterity and adaptivity in robot navigation, we need to take into account the decentralized mechanisms which exploit physical system-environment interactions. In this paper, by introducing a few underactuated locomotion systems, we explain (1) how mechanical body structures are related to motor control in locomotion behavior, (2) how a simple computational control process can generate complex locomotion behavior, and (3) how a motor control architecture can exploit the body dynamics through a learning process. Based on the case studies, we discuss the challenges and perspectives toward a new framework of adaptive robot control. © Springer-Verlag Berlin Heidelberg 2007.

基于解耦控制的SCARA机器人轨迹跟踪控制器设计

SCARA型机器人的控制问题由于其动力学模型中没有重力矩项的作用而得以简化,由于在实际应用中经常要求其高速运动,则对具有强耦合的哥氏力与向心力的控制就成为制约其系统性能的重要问题。提出通过线性变换对机器人系统解耦,将高阶系统转化为解耦的低阶系统进行控制的方法,并且应用极点配置对解耦的系统求解机器人控制器。该方法无需测量关节速度和加速度,只需要测量关节位置信号。所提出的控制器既能保证闭环系统全局渐进稳定,又能通过对线性化系统闭环极点的配置来获得期望的闭环系统响应性能。仿真实验证明了所提出的控制器设计方法的可行性。

基于B/S模式的机器人监控平台的研究

针对目前移动机器人本体研究平台存在局限性的问题,设计出一种基于B/S模式的机器人软件控制系统。系统的实现采用了Java和Vc相结合的方式,在利用Java语言的JNI技术解决接口问题的同时,为了充分利用现有软件模块,提出了一种新型的控制架构,使得整个系统更加完善。通过实验验证了此方法的有效性,有效的提高了系统的可维护性,可扩展性以及可复用性,最终很好实现了控制机器人的目的。

高性能机器人控制系统的研究

本文介绍了高性能机器人控制器的研制情况.该系统具有较高的控制精度,可完成对机器人和多个外部轴的协调控制.为便于国内用户使用,实现了中文界面功能键驱动的汉字编程示教盒.为适应机器人生产线的需要,提供了丰富的联网功能和生产线监控诊断功能.目前该系统已用于新松公司的6kg工业机器人产品中.

井下救援机器人控制系统的仿真与实现

本论文以新松公司和山东省科学院的《井下探测救援机器人的研究》项目为依托，展开井下探测救援机器人控制系统的研究。 我国的煤炭资源十分丰富，是世界上最大的煤炭生产国和消费国。我国煤矿大多数为矿工开采，不安全因素很多，矿井自然条件差，加上技术和管理等诸多方面不到位，使得我国煤矿矿井灾害事故频繁发生，人员伤亡十分惨重，煤矿安全形势已经十分严峻。 传统的救援方法只能通过提升绞车、移动式风车等设备清除垃圾，向井下通风，然后再搜救遇险矿工。这种方式危险性大，伤亡人数多，救援周期长，效率低。因此，迫切需要研发替代或部分替代救险队员进入矿井灾害现场进行环境探测和完成搜救任务的煤矿救援机器人，这对煤矿安全生产，建立特种危险环境下的工业救援体系具有十分重要的意义。 本文以沈阳新松公司的井下救援机器人为研究对象，对移动机器人控制体系结构进行了研究。主要工作如下： 从分析当前的体系结构入手，针对井下救援机器人的具体特点和设计要求，设计了一种以混合式体系结构为基础的移动机器人分布式体控制器。这种结构使用一种基于服务的概念，各个服务提供相当的功能，任意组合服务可以获得相应功能的机器人控制器。服务内部基于纵向的层次划分和横向的功能划分，并融合了特定的反应式行为。 本系统的特点是：自主与监控相结合，动作与感知相结合的行为，采用分布式程序的开发方法并且具有相当程度的开放性。在微软的机器人开发仿真平台上对该体系进行了实验仿真，并在新松公司井下救援机器人开发中实现了该系统。