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.     

Vehicle Teleoperation Interfaces

Despite advances in autonomy, there will always be a need for human involvement in vehicle teleoperation. In particular, tasks such as exploration, reconnaissance and surveillance will continue to require human supervision, if not guidance and direct control. Thus, it is critical that the operator interface be as efficient and as capable as possible. In this paper, we provide an overview of vehicle teleoperation and present a summary of interfaces currently in use.     

移动机器人条件反射能力的实现

Brooks的包容体系结构中,移动机器人控制器各个行为之间的关系是固定不变 的,可以看作实现了机器人的非条件反射能力,因此控制系统没有适应性．本文提出了条件 反射能力的实现方法,该方法能够和包容体系结构紧密结合,增强移动机器人的适应能力． 实验证明该方法是可行的．     

Supervisory control of multiple robots in dynamic tasking environments

A military targeting environment was simulated to examine the effects of an intelligent route-planning agent RoboLeader, which could support dynamic robot re-tasking based on battlefield developments, on the performance of robotics operators. We manipulated the level of assistance (LOAs) provided by RoboLeader as well as the presence of a visualisation tool that provided feedback to the participants on their primary task (target encapsulation) performance. Results showed that the participants' primary task benefited from RoboLeader on all LOAs conditions compared to manual performance; however, visualisation had little effect. Frequent video gamers demonstrated significantly better situation awareness of the mission environment than did infrequent gamers. Those participants with higher spatial ability performed better on a secondary target detection task than did those with lower spatial ability. Finally, participants' workload assessments were significantly lower when they were assisted by RoboLeader than when they performed the target entrapment task manually. Practitioner Summary: This study demonstrated the utility of an intelligent agent for enhancing robotics operators' supervisory control performance as well as reducing their workload during a complex urban scenario involving moving targets. The results furthered the understanding of the interplay among level-of-autonomy, multitasking performance and individual differences in military tasking environments.     

室内移动机器人超声传感器导航网络分布研究

对于室内广域移动机器人,超声波传感器网络是能够保证给定导航准确度的一种有效方法。合理的超声波传感器网络分布是实现超声波网络导航的重要条件。论述了超声波网络合理分布的原则,据此提出并分析了获得合理超声波传感器网络分布的四个步骤,仿真试验结果验证了它的有效性。     

Rolling and swaying motion estimation for a mobile robot by using omnidirectional optical flows

Described here is a method for estimating rolling and swaying motions of a mobile robot using optical flow. We have proposed an image sensor with a hyperboloidal mirror for the vision-based navigation of a mobile robot. Its name is HyperOmni Vision. The radial component of optical flow in HyperOmni Vision has a periodic characteristic. The circumferential component of optical flow has a symmetric characteristic. The proposed method makes use of these characteristic to estimate robustly the rolling and swaying motion of the mobile robot. Correspondence to: Y. Yagi e-mail: y-yagi@sys.es.osaka-u.ac.jp     

基于工业PC的六轴机器人控制系统设计

本文设计了一套基于PC的六轴机器人控制系统，叙述了系统的功能、逻辑结构、硬件组成、软件架构和安全措施等。此控制系统具有较好的开放性，在实际运行中工作平稳，安全可靠，并具有高扩展性能。     

冗余度机器人运动模型的神经网络辨识及实现

为提高网络学习速度,提出了一种新的动态神经网络结构——状态延迟输入动态递归神经网络.以德国PowerCube^TM模块化机器人为研究对象,将机器人系统返回的关节位置信息和OPTOTRAK30203维运动测量系统测得的机器人末端位置信息作为神经网络的学习样本,对包含各种影响因素的机器人运动模型进行了辨识,所得结果及误差分析,说明了SDIDRNN在学习能力上的优越性.     

形状记忆合金电机在机器人中的应用研究

作为新型功能材料的形状记忆合金(SMA)在工程机械和日常生活中得到了广泛的应用。由SMA构成的结构简单、控制灵活、功率密度大的电机(SMAA)，在机器人系统中具有独特的技术优势。文中详细阐明了SMAA的独特优点和结构类型．综述在机器人中的应用。