Hierarchical planning with state abstractions for temporal task specifications

Autonomous Robots - We often specify tasks for a robot using temporal language that can include different levels of abstraction. For example, the command “go to the kitchen before going to...     

Hierarchical task network and operator-based planning: two complementary approaches to real-world planning

Work on generative planning systems has focused on two diverse approaches to plan construction. Hierarchical task network (HTN) planners build plans by successively refining high-level goals into lower-level activities. Operator-based planners employ means-end analysis to directly formulate plans consisting of low-level activities. While many have argued the universal dominance of a single approach, this paper presents an alternative view: that in different situations either may be most appropriate. To support this view, a number of advantages and disadvantages of these approaches are described in light of experiences in developing two real-world, fielded planning systems.     

Linear programming as a tool for office automation planning

The “shadow costs” capability of Linear Programming (LP) provides office Automation (OA) managers with an instrument that determines optimal future allocations of money for resources such as computer workstatiions, software, training, awareness sessions, and user support. The approach can be implemented at any stage of OA development and based on current experience predicts how future restricted expenditures of money should be allocated among the listed resources in order to achieve the greatest return.     

Hierarchical task analysis: developments, applications, and extensions

Hierarchical task analysis (HTA) is a core ergonomics approach with a pedigree of over 30 years continuous use. At its heart, HTA is based upon a theory of performance and has only three governing principles. Originally developed as a means of determining training requirements, there was no way the initial pioneers of HTA could have foreseen the extent of its success. HTA has endured as a way of representing a system sub-goal hierarchy for extended analysis. It has been used for a range of applications, including interface design and evaluation, allocation of function, job aid design, error prediction, and workload assessment. Ergonomists are still developing new ways of using HTA which has assured the continued use of the approach for the foreseeable future.     

Hierarchical Task Network planning with common-sense reasoning for multiple-people behaviour analysis

Safety on public transport is a major concern for the relevant authorities. We address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.     

基于任务网络计划技术的煤矿企业应急管理方法

为提高煤矿企业应急管理的规范性和自动化程度,解决应急预案和应急决策的衔接问题,提出了一种基于网络计划技术的煤矿企业应急管理方法。该方法首先以应急预案的可重构性为基础,对应急预案进行规范化处理,采用任务网络计划技术将各个应急措施作为任务形成应急预案计划,然后将应急预案计划作为应急处置计划的模板,综合考虑突发事件的类型、具体情况、应急处置的资源条件及适度的个人偏好,在应急预案计划的基础上进行修正,迅速形成完整、规范的应急处置计划。实际应用表明,该方法可提高应急预案和应急执行计划的结构化和数字化水平,能够实现应急预案和应急执行计划的无缝衔接。     

Hierarchical production planning for complex manufacturing systems

A hierarchical approach to production planning for complex manufacturing systems is presented. A single facility comprising a number of work-centers that produce multiple part types is considered. The planning horizon includes a sequence of time periods, and the demand for all part types is assumed known. The production planning problem consists of minimizing the holding costs for all part types, as well as the work-in-process and the backlogging costs for the end items. We present a two-level hierarchy that is based on aggregating parts to part families, work-centers to manufacturing cells and time periods to aggregate time periods. The solution at the aggregate level is imposed as a constraint to the detailed level problems which are formulated for each manufacturing cell separately. This architecture uses a rolling horizon strategy to perform the production management function. We have employed perturbation analysis techniques to adjust certain parameters of the optimization problems at the detailed level to reach a near-optimal detailed production plan. Numerical results for several realistic example problems are presented and the solutions obtained from the hierarchical and monolithic approaches are compared. The results indicate that the hierarchical approach offers major advantages in computational efficiency, while the loss of optimality is acceptable.     

Hierarchical stochastic production planning for the highest business benefit

This paper addresses the hierarchical stochastic production planning (HSPP) problem of flexible automated workshops (FAWs), each with a number of flexible manufacturing systems (FMSs) the part-transfer between which is a delay of a time period. The problem not only includes uncertainties in the demand, capacities, material supply, processing times, necessity for rework, and scrap, but also considers multiple products and multiple time periods. The objective is to develop a production plan which tells each FMS how many parts to produce and when to produce them so as to obtain the highest business benefit. Herein, the HSPP problem is formulated by a stochastic nonlinear programming model whose constraints are linear but whose objective function is piecewise linear. For the convenience of solving the stochastic nonlinear programming model above, it is approximately transformed into a deterministic nonlinear programming model and further into a linear programming model. Because the scale of the model for a general workshop is too large to be solved by the simplex method on a personal computer within acceptable time, Karmarkar's algorithm and an interaction/prediction algorithm, respectively, are used to solve the model, the former for the medium or small scale problems and the latter for the large scale problems. By the implementation of the above-mentioned algorithms and through many HSPP examples, Karmarkar's algorithm, the interaction/prediction algorithm and the linear programming method in Matlab 5.0 are compared, the result of which shows that the proposed approaches are very effective and suitable for not only “push” production but also “pull” production.     

基于两阶段迭代优化的空天观测资源协同任务规划方法

为提高空天观测资源协同观测能力,基于分而治之框架,提出一种两阶段迭代优化方法以解决空天观测资源协同任务规划问题.第1阶段,根据观测机会和冲突度构造适应度函数,基于适应度将任务分配到合适的子规划中心;第2阶段,子规划中心根据分配到的任务进行资源调度,得到各类观测资源的观测计划,并将资源观测方案和观测收益反馈给第1阶段.第...     

TOPES: timeshared office planning and engineering system

A computer-aided interactive graphics system that addresses the sequence of steps in planning and designing office space has been developed for Bell System planning engineers. TOPES (telephone office planning and engineering system) is currently in use for planning and engineering Bell System equipment buildings. It is used for tasks ranging from graphics editing and interactive graphics teleconferencing to creating drawings files capable of supplying equipment engineering data, equipment inventories and other planning information.     

Hierarchical energy monitoring for task mapping in many-core systems

This work addresses a research subject with a rich literature: task mapping in NoC-based systems. Task mapping is the process of selecting a processing element to execute a given task. The number of cores in many-core systems increases the complexity of the task mapping. The main concerns in task mapping in large systems include (i) scalability; (ii) dynamic workload; and (iii) reliability. It is necessary to distribute the mapping decision across the system to ensure scalability. The workload of emerging many-core systems may be dynamic, i.e., new applications may start at any moment, leading to different mapping scenarios. Therefore, it is necessary to execute the mapping process at runtime to support a dynamic workload assignment. The workload assignment plays an important role in the many-core system reliability. Load imbalance may generate hotspots zones and consequently thermal implications, which may generate hotspots zones and consequently thermal implications. More recently, task mapping techniques aiming at improving system reliability have been proposed in the literature. However, such approaches rely on centralized mapping decisions, which are not scalable. To address these challenges, the main goal of this work is to propose a hierarchical runtime mapping heuristic, which provides scalability and a fair workload distribution. Distributing the workload inside the system increases the system reliability in long-term, due to the reduction of hotspot regions. The proposed mapping heuristic considers the application workload as a function of the consumed energy in the processors and NoC routers. The proposal adopts a hierarchical energy monitoring scheme, able to estimate at runtime the consumption at each processing element. The mapping uses the energy estimated by the monitoring scheme to guide the mapping decision. Results compare the proposal against a mapping heuristic whose main cost function minimizes the communication energy. Results obtained in large systems, up to 256 cores, show improvements in the workload distribution (average value 59.2%) and a reduction in the maximum energy values spent by the processors (average value 32.2%). Such results demonstrate the effectiveness of the proposal.     

Cognitive simulation as a tool for cognitive task analysis

Cognitive simulations are runnable computer programs that represent models of human cognitive activities. We show how one cognitive simulation built as a model of some of the cognitive processes involved in dynamic fault management can be used in conjunction with small-scale empirical data on human performance to uncover the cognitive demands of a task, to identify where intention errors are likely to occur, and to point to improvements in the person-machine system. The simulation, called Cognitive Environment Simulation or CES, has been exercised on several nuclear power plant accident scenarios. Here we report one case to illustrate how a cognitive simulation tool such as CES can be used to clarify the cognitive demands of a problem-solving situation as part of a cognitive task analysis.     

Hierarchical stochastic production planning for flexible automation workshops

This paper presents the hierarchical stochastic production planning (HSPP) problem for flexible automation workshops (FAWs) in agile manufacturing environments, which is a multiple-period multiple-product problem with random material supply, demands, capacities, processing times, rework and waste products. To solve the HSPP problem, a mathematical model is built up first. Then, an algorithm for HSPP is deduced in detail by using a stochastic interaction/prediction approach. The corresponding software package named as stochastic interaction/prediction algorithm (SIPA) has been developed and is presented in this paper, through which examples of HSPP have been studied, and which show that the algorithm can optimally decompose medium-term random product demand plans of an FAW into short-term stochastic production plans to be executed by FMSs in the FAW. Finally, the application of the algorithm is presented in detail through one of those examples.     

A method for measuring pilot workload based on task analysis

This paper presents a method for measuring pilot workload based on task analysis in order that the cockpit can be designed more reasonably. In addition, a prototype system is developed to use this method for the assessment of pilot workload. The method breaks the pilot's mission into several phases, segments, functions and tasks. And break pilot workload into 6 components using Wickens' multi-resource theory, which are vision(V), vision goggles(G), auditory sensation(A), cognitive activity(C), psychomotor activity(P) and kinesthesis(K). All missions consist of those tasks and each task have 6 workload components. The workload components for each task have been acquired by a study on many pilots, so workload can be assessed. A mission analysis database is built, and the prototype system can simulate pilot's flight process and evaluate workload.     

飞行器分层势场路径规划算法

传统势场法是飞行器路径规划的一种常用方法,但是存在目标不可达、易收敛到局部极小值和无评价机制等问题.本文针对这些问题提出了一种飞行器路径规划的分层势场算法.利用分段思想对势场函数进行修正,解决了目标不可达问题.引入回环力和飞行器间作用力,解决了易收敛到局部极小值问题和飞行器间的碰撞问题.采用分层方法,建立了多层次多方位路径点阵,并以此计算最优路径点,从而引入了势场法的评价机制.通过数值仿真,对在复杂障碍环境中的飞行器路径规划进行了传统势场法、改进势场法和分层势场法的对比研究.仿真结果验证了所提出的分层势场算法的有效性和可行性.