Telerobotic visual servoing

This paper addresses the problem of integrating the human operator with autonomous robotic visual tracking and servoing modules. A CCD camera is mounted on the end-effector of a robot and the task is to servo around a static or moving rigid target. In manual control mode, the human operator, with the help of a joystick and a monitor, commands robot motions in order to compensate for tracking errors. In shared control mode, the human operator and the autonomous visual tracking modules command motion along orthogonal sets of degrees of freedom. In autonomous control mode, the autonomous visual tracking modules are in full control of the servoing functions. Finally, in traded control mode, the control can be transferred from the autonomous visual modules to the human operator and vice versa. This paper presents an experimental setup where all these different schemes have been tested. Experimental results of all modes of operation are presented and the related issues are discussed. In certain degrees of freedom (DOF) the autonomous modules perform better than the human operator. On the other hand, the human operator can compensate fast for failures in tracking while the autonomous modules fail. Their failure is due to difficulties in encoding an efficient contingency plan.     

A Semi-Autonomous Reactive Control Architecture

This paper presents a novel intelligent control architecture for semi-autonomous systems. A semi-autonomous system is defined here as that autonomous system (machine) which interacts intelligently with a human user (collaborator) who might command, modify, or override its behavior. This work has been motivated by the need for a control architecture that can interact with human users of different perceptual and cognitive capabilities. A dynamic arbitration layer forms the core of the proposed architecture. Accordingly, the architecture evolves around three main variables: degree of autonomy to reflect the user's capabilities, user's level of confidence in commanding the machine, and strength of conflict between the user's command and the machine's autonomous command. The analogy between this architecture and horseback riding is presented and finally a demonstrative application example of a robotic wheelchair is given.     

Autonomy and metrics of autonomy

The quest for autonomy has been a pervasive theme in human culture through-out history. In this paper a general definition of autonomous systems is presented and discussed that leads naturally to the establishment of metrics to measure the level of autonomy of a system. This definition is based on the systems ability to achieve goals under uncertainties and it does not involve the means by which the goals are achieved, such as sensing and feedback. This paper takes the point of view that any autonomous system is a control system, and that to achieve higher levels of autonomy one may need to add methods traditionally developed in areas such as operations research and AI. The work presented here is based on earlier work by the author on functional architectures for autonomous spacecrafts.     

Modeling and constraining human interactions in shared controlutilizing a discrete event framework

Human integration is essential in systems where autonomous control alone would not be successful. In this paper, we present a framework for integrating a human supervisor into an otherwise autonomous control system. To facilitate integration, discrete event systems theory is adopted to model human interactions. It is via this interaction model that human commands can be combined with commands from an automated control system. For control synthesis, a method based on constraints is being used to generate velocity commands from the autonomous task level controller. The constraints are also utilized to limit human input so that erroneous human input is minimized. The methods are demonstrated by experiments     

Semi-autonomous shared control of large-scale manipulator arms

Semi-autonomous operation with shared control between the human operator and control computer has been developed and examined for a large-scale manipulator for gripping and lifting heavy objects in unstructured dynamical environments. The technique has been implemented on an electro-hydraulic actuated crane arm with redundant kinematic structure. Several modes of automation and interaction were evaluated. Experiments show satisfactory smoothness in the transitions between autonomous, shared and manual control, doubled performance in log loading for inexperienced operators while experienced operators reported reduced workload.     

Wheelchair for physically disabled people with voice,ultrasonic and infrared sensor control

This paper describes a wheelchair for physically disabled people developed within the UMIDAM Project. A dependent-user recognition voice system and ultrasonic and infrared sensor systems has been integrated in this wheelchair. In this way we have obtained a wheelchair which can be driven with using voice commands and with the possibility of avoiding obstacles and downstairs or hole detection. The wheelchair has also been developed to allow autonomous driving (for example, following walls). The project, in which two prototypes have been produced, has been carried out totally in the Electronics Department of the University of Alcalá (Spain). It has been financed by the ONCE. Electronic system configuration, a sensor system, a mechanical model, control (low level control, control by voice commands), voice recognition and autonomous control are considered. The results of the experiments carried out on the two prototypes are also given.     

融合类人驾驶行为的无人驾驶深度强化学习方法

现有无人车辆的驾驶策略过于依赖感知-控制映射过程的“正确性”,而忽视了人类驾驶汽车 时所遵循的驾驶逻辑。该研究基于深度确定性策略梯度算法,提出了一种具备类人驾驶行为的端到端 无人驾驶控制策略。通过施加规则约束对智能体连续行为的影响,建立了能够输出符合类人驾驶连续 有序行为的类人驾驶端到端控制网络,对策略输出采用了后验反馈方式,降低了控制策略的危险行为 输出率。针对训练过程中出现的稀疏灾难性事件,提出了一种更符合控制策略优化期望的连续奖励函 数,提高了算法训练的稳定性。不同仿真环境下的实验结果表明,改进后的奖励塑造方式在评价稀疏 灾难性事件时,对目标函数优化期望的近似程度提高了 85.57%,训练效率比传统深度确定性策略梯度 算法提高了 21%,任务成功率提高了 19%,任务执行效率提高了 15.45%,验证了该方法在控制效率和 平顺性方面具备明显优势,显著减少了碰撞事故。     

Cooperative autonomous driving: intelligent vehicles sharing city roads

The paper presents the Intelligent Control System Laboratory's (ICSL) Cooperative Autonomous Mobile Robot technologies and their application to intelligent vehicles for cities. The deployed decision and control algorithms made the road-scaled vehicles capable of undertaking cooperative autonomous maneuvers. Because the focus of ICSL's research is in decision and control algorithms, it is therefore reasonable to consider replacing or upgrading the sensors used with more recent road sensory concepts as produced by other research groups. While substantial progress has been made, there are still some issues that need to be addressed such as: decision and control algorithms for navigating roundabouts, real-time integration of all data, and decision-making algorithms to enable intelligent vehicles to choose the driving maneuver as they go. With continued research, it is feasible that cooperative autonomous vehicles will coexist alongside human drivers in the not-too-distant future.     

一种卫星温度自主管理的优化设计

温度自主管理是卫星主动式热控的主要表现形式,温度自主管理系统将接收到的被控设备的温度数据和固化在软件中的温度阈值进行比较后,发出相应的指令控制加热器的通或断,从而确保星上设备或部件的温度始终保持在一个合理的范围内,不会因为温度过高或过低影响卫星的可靠性和安全性,在一些卫星中,部分被控设备的接口发生了变化,传统的自主管理系统在新接口的温度控制上存在一定缺陷,导致地面测试中出现了热控回路报警,采用增加同一加热器回路通断指令的自主重试次数的方法对温度自主管理软件进行了优化,经过实验验证,优化后的温度自主管理系统能够很好地适应新的接口,该系统已经在多个卫星中成功应用,可为后续卫星提供参考。     

Training of a leaning agent for navigation--inspired by brain-machine interface.

The design clue for the remote control of a mobile robot is inspired by the Talwar's brain-machine interface technology for remotely training and controlling rats. Our biologically inspired autonomous robot control consciousness-based architecture (CBA) is used for the remote control of a robot as a substitute for a rat. CBA is a developmental hierarchy model of the relationship between consciousness and behavior, including a training algorithm. This training algorithm computes a shortcut path to a goal using a cognitive map created based on behavior obstructions during a single successful trial. However, failures in reaching the goal due to errors of the vision and dead reckoning sensors require human intervention to improve autonomous navigation. A human operator remotely intervenes in autonomous behaviors in two ways: low-level intervention in reflexive actions and high-level ones in the cognitive map. Experiments are conducted to test CBA functions for intervention with a joystick for a Khepera robot navigating from the center of a square obstacle with an open side toward a goal. Their statistical results show that both human interventions, especially high-level ones, are effective in drastically improving the success rate of autonomous detours.     

自主轮式机器人THMR－V的混合模糊逻辑控制

轮式机器人的控制问题是控制研究的关键问题之一，对高速自主导航的轮式机器人，控制器的实时性、精确性和鲁棒性要求很高．在本文中，根据PID控制和模糊逻辑控制的各自优点，将传统的PID控制与模糊逻辑控制结合起来，提出了一种混合模糊逻辑控制算法. 经实验检验，该算法具有很高的实时性、控制精度和鲁棒性，能够满足机器人高速自主导航的需要．     

Electronic control for a wheel-chair guided by oral commands and ultrasonic and infrared sensors

This paper describes a wheelchair for physically disable people. In this wheelchair, a dependent-user recognition voice system and ultrasonic and infrared sensor systems have been integrated. In this way, the wheelchair can be driven whit oral commands and with the possibility of obstacle avoidance and downstairs or hole detection. The wheelchair allows autonomous driving (for example following walls). This project has been developed in the Electronic Department of the Alcala University and it has been financed by the ONCE Foundation. The electronic control system we have built allows an easy and handy driving with the only use of the human voice. The system drives itself through structured environments (hospitals, rehabilitation centers and so on). System structure is in a way that is possible to add more features, easy and economically (like appliance control, door opening and closing and other telecontrol, etc.).     

Autonomous decentralized control and its application to the rapid transit system

A large scale control system has three intrinsic requirements of fault tolerance, on-line extension and maintenance for non-stop operation. For attaining these requirements, the new design philosophy for autonomous decentralized control system, called HAL (Harmonous, Autonomous and Localities) concept, has been proposed based on the biological analogy.The viewpoint of this concept is that it is quite normal for a system to have failed parts.Sufficient conditions for an autonomous decentralized control system are given that every subsystem is uniform and equal in function and structure, and utilizes only local information for control and coordination.As one of the applications to the system components of this new concept, ADL-Net (Autonomous Decentralized Loop Network) has been developed, where fault tolerance of the system is attained by giving autonomy for fault detection, recovery and transmission to every network control processor.The HAL concept has also been applied to the train traffic control system for subways with three intrinsic requirements for supporting their non-stop operations.     

Hovering control of model helicopter by vision

In this paper, we introduce an autonomous flying model helicopter with a vision control system. A feature of the helicopter is that autonomous hovering is realized by a vision control system. Owing to this vision control system, the model helicopter is able to take off, land, and hover without any human assistance. The vision control sstem is composed of a CCD camera mounted on the helicopter and an image processor on the ground. We first introduce the configuration of the helicopter system, which has a vision sensor, a clinometer, and an azimuth sensor. To determine the 3-D position and posture of helicopter, a technique of image recognition using a monocular image is used. Finally, we give an experiment result which we obtained in a hovering test with the vision control system. This result shows the effectiveness of the vision control system in the model helicopter.     

AN AI ELECTRICAL GROUND SUPPORT EQUIPMENT FOR CONTROLLING AND TESTING A SPACE INSTRUMENT

A versatile and modular electrical ground support equipment (EGSE) system has been developed using artificial intelligence (AI) techniques to control and test the PESCA instrument and the communication process of the satellite without any human supervision. The PESCA instrument has been designed and built with the purpose of studying solar energetic particles and the anomalous cosmic rays. It will be part of the Russian FOTON satellite payload that is scheduled to be launched in December 2007. The tool allows complete and autonomous control, verification, and validation of the PESCA instrument, although its modularity makes it extensible to other onboard instruments.     

Overcoming underload and overload: The effect of stage and level of autonomy in routine-failure trade-off in human-autonomy teams

We examined how human mental workload and the corresponding eye movement behaviors are affected by the stages and levels of autonomy in routine and autonomy failure conditions in human-autonomy teams (HAT). Thirty participants performed monitoring and diagnosing tasks with the autonomous agent in a three-factor experiment. The factors included information processing stage, level of autonomy, and agent operation condition. The results indicated that the later the agent-supported information processing stage or the higher the autonomy level, the higher the participants’ mental workload following autonomous agent failure. Compared to the continuous manual operation condition, the HAT performance did not decline following autonomous agent failure at the cost of increased mental workload. The eye movement results indicated a top-down compensatory control mechanism of attention, indicating the risk of team performance decline following autonomous agent failure. These findings can be applied in designing autonomous agents and setting human mental workload levels in a HAT.     

Multi-robot cooperation in the MARTHA project

The MARTHA project objectives are the control and the management of a fleet of autonomous mobile robots for transshipment tasks in harbors, airports and marshalling yards. One of the most challenging and key problems of the MARTHA project is multi-robot cooperation. A general concept for the control of a large fleet of autonomous mobile robots has been developed, implemented and validated in the framework of the MARTHA project. This is the first study in the autonomous mobile robot field to add multi-robot cooperation capabilities to such a large fleet of robots     

Fuzzy logic steering control of autonomous vehicles inside roundabouts

The expansion of roads and the development of new road infrastructures have increased in recent years, linked to the population growing in large cities. In the last two decades, roundabouts have largely replaced traditional intersections in many countries. They have the advantage of allowing drivers continuous flow when traffic is clear, without the usual delay caused by traffic lights. Although roundabouts with and without traffic-signal control have been widely used and considered in the literature, driverless control on roundabouts has not been studied in depth yet. The behavior of autonomous vehicles in roundabouts can be divided into three stages: entrance, inside, and exit. The first and last may be handled as an extension of intersections. However, autonomous driving on the roundabout requires special attention. In this paper, the design and implementation of a fuzzy logic system for the steering control of autonomous vehicles inside the roundabout is proposed. Cascade architecture for lateral control and parametric trajectory generation are used. Fuzzy control has proved to be easy to define using expert knowledge. Experiments with a real prototype have been carried out, taking into account different speed profiles and lane change maneuvers inside the roundabout, with very satisfactory results.     

Cooperative controllers for highways based on human experience

The AUTOPIA program has been working on the development of intelligent autonomous vehicles for the last 10 years. Its latest advances have focused on the development of cooperative man?uvres based on communications involving several vehicles. However, so far, these man?uvres have been tested only on private tracks that emulate urban environments. The first experiments with autonomous vehicles on real highways, in the framework of the grand cooperative driving challenge (GCDC) where several vehicles had to cooperate in order to perform cooperative adaptive cruise control (CACC), are described. In this context, the main challenge was to translate, through fuzzy controllers, human driver experience to these scenarios. This communication describes the experiences deriving from this competition, specifically that concerning the controller and the system implemented in a Citröen C3.     

基于VR的自由飞行空间机器人自主运动规划仿真系统

该文研究了基于VR的自由飞行空间机器人（FFS）自主运动规划仿真系统技术。首先提出了一种增强型虚拟现实系统方案,并重点研究了有关FFSR的虚拟建模和自主运动规划控制技术,最后进行了基于VR的FFSR自主运动规划际统仿真。