Automated procedure execution for space vehicle autonomous control

Increased operational autonomy and reduced operating costs have become critical design objectives in next-generation NASA and Department of Defense (DoD) space programs. Our objective is to develop a semiautomated system for intelligent spacecraft operations support. This paper presents the Spacecraft Operations and Anomaly Resolution System (SOARS) as a standardized, model-based architecture for performing High-Level Tasking, Status Monitoring and automated Procedure Execution Control for a variety of spacecraft. The particular focus here is on the Procedure Execution Control module. A hierarchical procedure network is proposed as the fundamental means for specifying and representing arbitrary operational procedures. A separate procedure interpreter controls automatic execution of the procedure, taking into account the current status of the spacecraft as maintained in an object-oriented spacecraft model.     

Depth control for an over-actuated,hover-capable autonomous underwater vehicle with experimental verification

A PI-D based control system is developed for over-actuated, hover-capable AUVs which enables a smooth transition from hover-style to flight-style operation with system stability and convergence proven using a Lyapunov approach. The performance of the controller is demonstrated by simulation and is verified through experiments. The approach is able to operate over a range of vehicle ballasting configurations, and to imposed external disturbances. The proposed system is computationally inexpensive and does not require a detailed hydrodynamic model to implement. By monitoring the energy consumption on board, the cost of maintaining depth at a range of forward speeds with different buoyancy conditions can be quantified, and their impact on the cost of transport is highlighted for future optimisation of energy consumption.     

灰色PID控制在AUV横滚控制中应用研究

针对AUV航行环境复杂、模型参数摄动大、执行机构的饱和非线性等特点,采用灰色预测算法改进传统的AUV PID横滚姿态控制器,设计了灰色PID控制算法,以达到抑制和消除横滚的目的。仿真结果表明,灰色预测PID算法操舵平滑,控制速度快,鲁棒性和环境适应能力更好,完全能胜任AUV横滚姿态控制的要求。     

水下自主航行器的横滚抑制控制系统设计

水下自主航行器受到扰动影响容易产生横滚,为了提高水下航行器的稳定性,提出一种基于横滚抑制的水下自主航行器控制系统设计方法。系统设计主要包括了控制算法设计和系统的硬件模块化设计,采用鲁棒性PID控制算法进行控制律设计,构建静态神经元控制时滞闭环系统,采用严格反馈抑制方法进行横滚抑制,在程序加载电路中进行控制算法加载。硬件设计主要包括航行姿态的A/D采样电路、控制信息处理器、伺服机构和控制输出电路等。最后进行系统调试和仿真分析,结果表明,采用该控制系统能有效抑制水下自主航行器的横滚,进行姿态修正,提高航行稳定性。     

复杂涌流下水下自主航行器横滚抑制控制仿真

在复杂的海洋涌流背景下,水下自主推进航行器受到扰动较大,出现横滚导致控制稳定性下降,提出一种基于模糊PID扰动抑制的复杂涌流下水下自主航行器横滚抑制算法.构建在复杂涌流下的水下自主航行器运动状态模型,在航行器的纵向运动全包线内对横舵角、横滚角、回旋角等运动约束参量进行定常运动分析,采用模糊PID神经网络控制模型进行控制律的改进设计,结合Lyapunov稳定性原理进行横滚抑制和误差修正,实现控制算法改进.仿真结果表明,采用该控制算法进行复杂涌流下水下自主航行器横滚抑制控制,具有较好的输出响应跟踪性能,有效抑制横滚,提高了水下自主航行器的稳定控制能力,鲁棒性较好.     

自动驾驶车队出口道左转交叉口轨迹最优控制

出口道左转交叉口通过改变部分出口道的车道功能,可为左转交通提供额外的通行能力。本文基于传统跟驰模型和换道模型,建立以通行效率和车队运行稳定性为目标的最优控制模型,在Matlab环境下使用CasADi求解器中的BONMIN算法对模型进行求解。将常规交叉口放行策略与本文所提出的最优放行策略进行对比分析。结果表明,模型计算给出的3种通行策略不仅能合理使用对向出口车道,同时车辆通过交叉口的次序得以提前,从而使得交叉口的通行效率有一定程度的提升。     

System control of an autonomous planetary mobile spacecraft

Our goal is to suggest the scheduling and control functions necessary for accomplishing mission objectives of a fairly autonomous interplanetary mobile spacecraft, while maximizing reliability. Goals are (1) to provide an extensible, reliable system conservative in its use of on-board resources, while (2) getting full value from subsystem autonomy, and (3) avoiding the lure of ground micromanagement. We propose a functional layout consisting of four basic elements: Ground and System Executive system functions and Resource Control and Activity Manager subsystem functions. The system executive includes six subfunctions: System Manager, System Fault Protection, Planner, Schedule Adapter, Event Monitor, and Resource Monitor. The full configuration is needed for autonomous operation on Moon or Mars, whereas a reduced version without the planning, schedule adaption and event monitoring functions could be appropriate for lower-autonomy use on the Moon. An implementation concept is suggested which is conservative in use of system resources and consists of modules combined with a communications network. The paper introduces a language concept we have termed a “scheduling calculus” for rapidly performing essential on-board schedule adaption functions.     

Adaptive vehicle traction force control for intelligent vehicle highway systems (IVHSs)

This paper is concerned with robust longitudinal control of vehicles in intelligent vehicle highway systems by adaptive vehicle traction force control. Two different traction force controllers, adaptive fuzzy logic control and adaptive sliding-mode control, are proposed and applied to the fastest stable acceleration/deceleration and robust vehicle platooning problems. The motivation for investigating adaptive techniques arises from the unknown time-varying nature of the tire/road surface interaction that governs vehicle traction. Synchronous application of the engine or brake torques is also proposed for more stable vehicle maneuvers. The lack of controllability during braking (only one net input torque for the two control objectives, i.e., front and rear wheel slips) is partly overcome by applying auxiliary engine torque. Simulations of the two control methods are conducted using a complex nonlinear vehicle model which fully describes the dynamic behavior of the vehicle. Both controllers result in good performance under time-varying operating conditions.     

自主式水下航行器试验平台的设计

为水下探测提供试验平台,设计了一台自主式水下航行器(AUV)。该航行器可被应用于海洋资源调查、港口安防、水产养殖、地貌观测等诸多方面。它可利用自身搭载的声呐、AHRS等传感器,实现水下自主航行、避障;并通过导航算法,实时地规划最优路径,完成水下地貌观测、资源探测。同时它也具备在水下未知环境,构建地图能力。     

Development of vehicle maneuvering system for autonomous driving

Recently, autonomous driving technology has received significant interest, and consequently, various autonomous driving algorithms have been developed by researchers. An experimental (conventional) vehicle verifies the strategy for autonomous driving by testing the performance and feasibility of the corresponding algorithms. Implementation of the autonomous driving strategy in the conventional vehicle system requires modification of the electronic control unit (ECU); however, this is limited by security issues and the high cost of development.In this paper, a maneuvering system that can control the steering angle, braking force, and accelerating signal so that autonomous driving does not operate via the ECU is proposed. Because the steering angle is an important factor in terms of the vehicle motion behavior, a robust angle controller based on the disturbance observer is adopted. Moreover, to ensure safety and user convenience, a user intention recognition algorithm is proposed. Based on this algorithm, the maneuvering system can be disabled during control without using any perception sensor. Finally, several experiments are conducted to evaluate the functions of the maneuvering system. A scenario-based driving test is also performed to verify the feasibility of the maneuvering system.     

Real-time vision-based tracking control of an unmanned vehicle

Recent advances in manufacturing automation have motivated vision-based control of autonomous vehicles operated in unattended factories, material handling processes, warehouse operations, and hazardous environment explorations. Existing vision-based tracking control systems of autonomous vehicles, however, have been limited in real-time applications due to slow and/or expensive visual feedback and complicated dynamics and control with nonholonomic constraints. This paper presents a practical real-time sion-based cking control system of an unmanned vehicle, ViTra. Unlike the conventional RS170 video-based machine vision systems, ViTra uses a DSP-based flexible integrated vision system (FNS) which is characterized by low cost, computational efficiency, control flexibility, and a friendly user interface.

In particular, this paper focuses on developing a framework for vision tracking systems, designing generic fiducial patterns, and applying real-time vision systems to tracking control of autonomous vehicles. A laboratory prototype vision-based tracking system developed at Georgia Institute of Technology permits the uniquely designed fiducial landmarks to be evaluated experimentally, the control strategy and the path planning algorithm derived in the paper to be validated in real-time, and the issues of simplifying nonlinear dynamics and dealing with nonholonomic constraints to be addressed in practice. Experimental results reveal interesting insights into the design, manufacture, modeling, and control of vision-based tracking control systems of autonomous vehicles.     

面向AUV自主回收的单目视觉定位算法

针对自主水下航行器（AUV）自主回收过程中对回收装置的近距相对位置测量问题,提出了一种基于单目视觉的近距定位方法。该方法首先给出AUV与回收装置端面垂直时的单目定位方法,然后提出旋转定位法来解决AUV有俯仰和偏航时AUV与回收装置之间相对位置的精确计算问题,并进行了实验室试验研究,验证了该方法的有效性。     

基于激光雷达和SLAM的自主行驶小车设计

结合ROS平台、激光雷达和SLAM技术设计出拥有自主移动能力的行驶小车。首先搭建硬件开发平台,配置ROS下的一系列开源功能包,实现路径规划、自主行驶和避障功能。软件部分通过激光雷达的功能包获取周围的环境信息,进行SLAM地图创建,通过导航功能包进行全局路径规划和局部路径规划,小车行驶过程中结合AMCL功能包对移动过程中产生的误差进行修正,小车能够实现自主行驶。     

Measurements of BART magnetic fields with an automatic geomagneticpulsation index generator

Measurements of the large-amplitude magnetic field fluctuations produced by the San Francisco Bay Area Rapid Transit (BART) system using an automatic computer-based geomagnetic pulsation index generator located on the Stanford campus, which is approximately 40 km from the center of the BART system, are described. Because the temporal variation of the fluctuations is well defined on an hour-to-hour and day-to-day basis, due to the transit system scheduling, they provide a convenient means for evaluating the performance of the index generator. The index generator, in turn, provides new information about the frequency content of the BART field fluctuations, and it can be used, in a general sense, to monitor activity on the BART system     

A novel self adaptive-electric fish optimization-based multi-lane changing and merging control strategy on connected and autonomous vehicle

Wireless Networks - Merging areas on freeways are key locations due to vehicles’ fixed lateral differences. Though, such challenges are considerably unnecessary with connected and autonomous...     

Neural network based-time optimal sliding mode control for an autonomous underwater robot

This paper presents a robot control system using sliding mode control (SMC) as a core controller. The SMC switches according to the Pontryagin’s time optimal control principle, in which the solution is obtained by using neural network approach. The control system is implemented on Chalawan, a six-degree-of-freedom autonomous underwater robot developed at Mechatronics Laboratory, AIT. The control system can be applied to underwater robots, which have similar kind of architecture. Performance of the proposed controller is compared with various classical SMCs and conventional linear control system. The comparison detail results such as controller performance and error phase portrait are presented and analyzed. Such comparisons ensure the implementation success and prove it as a real time-optimal controller. The results also show the controller’s effective capabilities in plant nonlinearity and parameters uncertainties.     

Visual spatial attention control in an independent brain-computer interface

This paper presents a novel brain computer interface (BCI) design employing visual evoked potential (VEP) modulations in a paradigm involving no dependency on peripheral muscles or nerves. The system utilizes electrophysiological correlates of visual spatial attention mechanisms, the self-regulation of which is naturally developed through continuous application in everyday life. An interface involving real-time biofeedback is described, demonstrating reduced training time in comparison to existing BCIs based on self-regulation paradigms. Subjects were cued to covertly attend to a sequence of letters superimposed on a flicker stimulus in one visual field while ignoring a similar stimulus of a different flicker frequency in the opposite visual field. Classification of left/right spatial attention is achieved by extracting steady-state visual evoked potentials (SSVEPs) elicited by the stimuli. Six out of eleven physically and neurologically healthy subjects demonstrate reliable control in binary decision-making, achieving at least 75% correct selections in at least one of only five sessions, each of approximately 12-min duration. The highest-performing subject achieved over 90% correct selections in each of four sessions. This independent BCI may provide a new method of real-time interaction for those with little or no peripheral control, with the added advantage of requiring only brief training.     

SVM在自主履带车辆转向问题上的仿真研究

SVM(支持向量机)是一种应用广泛的机器学习分类、回归和完成其他学习任务的方法。文章简要介绍了支持向量机的原理,并以一维数据为基础,采用基于-不敏感损失函数的-SVR与基于最小二乘基本原理的曲线拟合法,在MATLAB平台下,对多项式函数、包含指数函数的三角函数分别进行回归比较。最后对多维数据的某型自主履带车辆转向角度进行回归预测。结果表明支持向量机的方法具有应用范围广、逼近精度高、泛化性能好的特点。     

A path tracking control system for autonomous mobile robots: an experimental investigation

A path tracking control system developed for autonomous mobile robots driven by wheels is described. In conventional approaches, the path is usually planned by smooth curves with curvature-continuity and a path tracking controller is independently designed to compensate the path error occurring in the navigation. However, smooth path planning is difficult to execute on-line due to the computational burden. In addition, the conventional path tracking algorithm often causes unpredictable tracking motion when large path error occurs. In previous work, the present authors presented a bang-bang path tracking algorithm by which smooth and stable tracking motion could be obtained even for the path given by simple combination of straight lines or circles and its effectiveness was proven via preliminary simulation studies. However, there still remained the problem that the design parameter called landing coefficient could not be optimally chosen and performance verification through real system application was not accomplished. In this study, we improve the algorithm which can determine the design parameters analytically and verify its performance by implementing the algorithm in an actual mobile robot control system designed using a personal computer. To investigate the performance of the control system, a series of path tracking experiments was conducted for a two-wheel driven robot developed in the laboratory.