Craig Schlenoff - Academia.edu (original) (raw)

Papers by Craig Schlenoff

The US Department of Defense has initiated plans for the deployment of autonomous robotic vehicle... more The US Department of Defense has initiated plans for the deployment of autonomous robotic vehicles in various tactical military operations starting in about seven years. Most of these missions will require the vehicles to drive autonomously over open terrain and on roads which may contain traffic, obstacles, military personnel as well as pedestrians. Unmanned Ground Vehicles (UGVs) must therefore be able to detect, recognize and track objects and terrain features in very cluttered environments.

We have tested a prototype dual-band NVG system consisting of two NVGs fitted with filters that s... more We have tested a prototype dual-band NVG system consisting of two NVGs fitted with filters that split the NVG sensitive range into a short (visual) and a long wavelength (NIR) band. The Color-the-night technique (see Hogervorst & Toet, SPIE D&S'08) was used to fuse the images of the two sensors. We designed a color scheme especially optimized for the detection of camouflaged targets. The added value of this system was evaluated in an experiment in which observers had to detect targets (green and blue tubes).

The rheological (flow) properties of concrete are important for the construction industry because... more The rheological (flow) properties of concrete are important for the construction industry because concrete is usually put into place in its plastic form. This importance can be attested to by the large body of literature existing on concrete rheology [1, 2, 3, 4]. Unfortunately, due to the complex composition of the material, no definite method for predicting the flow of concrete from its components exists.

Abstract This article discusses a newly formed IEEE-RAS working group entitled Ontologies for Rob... more Abstract This article discusses a newly formed IEEE-RAS working group entitled Ontologies for Robotics and Automation (ORA). The goal of this working group is to develop a standard ontology and associated methodology for knowledge representation and reasoning in robotics and automation, together with the representation of concepts in an initial set of application domains.

ABSTRACT The goal of the PSL (Process Specification Language) project at NIST is to develop a pro... more ABSTRACT The goal of the PSL (Process Specification Language) project at NIST is to develop a process specification" interlingua" for process information sharing across different applications in the manufacturing domain. A process model in PSL is to be composed of the PSL-CORE and a number of extensions that provide domain-specific or taskspecific constructs. Thus, the PSL extensions constitute the components to be developed, related, and reused for a complete service.

Abstract The IEEE RAS Ontologies for Robotics and Automation Working Group is dedicated to develo... more Abstract The IEEE RAS Ontologies for Robotics and Automation Working Group is dedicated to developing a methodology for knowledge representation and reasoning in robotics and automation. As part of this working group, the Industrial Robots sub-group is tasked with studying industrial applications of the ontology. One of the first areas of interest for this subgroup is the area of kit building or kitting.

As new technologies develop and mature, it becomes critical to provide both formative and summati... more As new technologies develop and mature, it becomes critical to provide both formative and summative assessments on their performance. Performance assessment events range in form from a few simple tests of key elements of the technology to highly complex and extensive evaluation exercises targeting specific levels and capabilities of the system under scrutiny. Typically the more advanced the system, the more often performance evaluations are warranted, and the more complex the evaluation planning becomes. Numerous evaluation frameworks have been developed to generate evaluation designs intent on characterizing the performance of intelligent systems. Many of these frameworks enable the design of extensive evaluations, but each has its own focused objectives within an inherent set of known boundaries.

Proceedings of the 8th …, Jan 1, 2008

Abstract On-road autonomous vehicle navigation requires real-time motion planning in the presence... more Abstract On-road autonomous vehicle navigation requires real-time motion planning in the presence of static and moving objects. Based on sensed data of the environment and the current traffic situation, an autonomous vehicle has to plan a path by predicting the future location of objects of interest. In this context, an object of interest is a moving or stationary object in the environment that has a reasonable probability of intersecting the path of the autonomous vehicle within a predetermined time frame. This paper investigates the ...

4D/RCS is a hierarchical architecture designed for the control of intelligent systems. One of the... more 4D/RCS is a hierarchical architecture designed for the control of intelligent systems. One of the main areas that 4D/RCS has been applied to recently is the control of autonomous vehicles. To accomplish this, a hierarchical decomposition of on-road driving activities has been performed which has resulted in implementation of 4D/RCS tailored towards this application. This implementation has seven layers and ranges from a journey manager which determines the order of the places you wish to drive to, through a destination manager which provides turn-by-turn directions on how to get to a destination, through a route segment, drive behavior, elemental maneuver, goal path trajectory, and then finally to servo controllers. In this paper, we show, within the 4D/RCS architecture, how knowledge-driven top-down symbolic representations combined with low-level bottom-up tasks can synergistically provide valuable information for on-road driving better than what is possible with either of them alone. We demonstrate these ideas using field data obtained from an Unmanned Ground Vehicle (UGV) traversing urban on-road environments.

Internet stranica: http://www. mel. nist. …, Jan 1, 1997

Abstract: The goal of the NIST Process Specification Language (PSL) project is to investigate and... more Abstract: The goal of the NIST Process Specification Language (PSL) project is to investigate and arrive at a common, unifying model of process which will ultimately be suitable for multiple process-related applications, yet powerful and robust enough to meet each set of requirements. This paper focuses on the second phase of the project, that of analyzing existing process representations to determine how well they represent the information requirements found in an earlier phase of the project.

Philadelphia, USA, Jan 1, 2004

Sensory processing for real-time, complex, and intelligent control systems is costly, so it is im... more Sensory processing for real-time, complex, and intelligent control systems is costly, so it is important to perform only the sensory processing required by the task. In this paper, we describe a straightforward metric for precisely defining sensory processing requirements. We then apply that metric to a complex, real-world control problem, autonomous on-road driving. To determine these requirements the system designer must precisely and completely define 1) the system behaviors, 2) the world model situations that the system behaviors require, 3) the world model entities needed to generate all those situations, and 4) the resolutions, accuracy tolerances, detection timing, and detection distances required of all world model entities.

Computational …, Jan 1, 2008

The National Institute of Standards and Technology (NIST) Intelligent Control of Mobility Systems... more The National Institute of Standards and Technology (NIST) Intelligent Control of Mobility Systems (ICMS) Program provides architectures and interface standards, performance test methods and data, and infrastructure technology needed by the U.S. manufacturing industry and government agencies in developing and applying intelligent control technology to mobility systems to reduce cost, improve safety, and save lives. The ICMS Program is made up of several areas including: defense, transportation, and industry projects, among others. Each of these projects provides unique capabilities that foster technology transfer across mobility projects and to outside government, industry and academia for use on a variety of applications. A common theme among these projects is autonomy and the Four Dimensional (3D + time)/Real-time Control System (4D/RCS) standard control architecture for intelligent systems that has been applied to these projects. This chapter will briefly describe recent project advances within the ICMS Program including: goals, background accomplishments, current capabilities, and technology transfer that has or is planned to occur. Several projects within the ICMS Program have developed the 4D/RCS into a modular architecture for intelligent mobility systems, including: an Army Research Laboratory (ARL) Project currently studying onroad autonomous vehicle control, a Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) Project studying learning within the 4D/RCS architecture with road following application, and an Intelligent Systems Ontology project that develops the description of intelligent vehicle behaviors. Within the standards and performance measurements area of the ICMS program, a Transportation Project is studying components of intelligent mobility systems that are finding their way into commercial crash warning systems (CWS). In addition, the ALFUS (Autonomy Levels For Unmanned Systems) project determines the needs for metrics and standard definitions for autonomy levels of unmanned systems. And a JAUS (Joint Architecture for Unmanned Systems) project is working to set a standard for interoperability between components of unmanned robotic vehicle systems. Testbeds and frameworks underway at NIST include the PRIDE (Prediction in Dynamic Environments) framework to provide probabilistic predictions of a moving object's future position to an autonomous vehicle's planning system, as well as the USARSim/MOAST (Urban Search and Rescue Simulation/Mobility Open Architecture Simulation and Tools) framework that is being developed to provide a comprehensive set of open source tools for the development and evaluation of autonomous agent systems. A NIST Industrial Autonomous Vehicles (IAV) Project provides technology transfer from the defense and transportation projects directly to industry through collaborations with automated guided vehicles manufacturers by researching 4D/RCS control applications to automated guided vehicles inside facilities. These projects are each briefly described in this Chapter followed by Conclusions and continuing work.

Chapter in the Climbing …, Jan 1, 2007

PRIDE is a hierarchical multiresolutional framework for moving object prediction that incorporate... more PRIDE is a hierarchical multiresolutional framework for moving object prediction that incorporates multiple prediction algorithms into a single, unifying framework. PRIDE is based upon the 4D/RCS (Real-time Control System) reference model architecture and provides information to planners at the level of granularity that is appropriate for their planning horizon. This framework supports the prediction of the future location of moving objects at various levels of resolution, thus providing prediction information at the frequency and level of abstraction necessary for planners at different levels within the hierarchy. To date, two prediction approaches have been applied to this framework. In this paper, we provide an overview of the PRIDE (Prediction in Dynamic Environments) framework and describe the approach that has been used to model different aggressivities of drivers. We then explore different aggressivity models to determine their impact on the location predictions that are provided through the PRIDE framework. We also describe recent efforts to implement PRIDE in USARSim, which provides high-fidelity simulation of robots and environments based on the Unreal Tournament game engine.

… 6081, National Institute of Standards and …, Jan 1, 1997

In April, 1997, the Process Specification Language (PSL) Project held a Roundtable discussion at ... more In April, 1997, the Process Specification Language (PSL) Project held a Roundtable discussion at the National Institute of Standards and Technology (NIST). The goals of the Roundtable was to assemble key champions and stakeholders of various approaches towards process representation in order to discuss the relative merits to reach consensus on a language architecture and to establish a technical approach for proceeding. It was agreed that the language architecture should be based upon a formal semantic foundation, upon which would be layered a number of syntactic mappings, each with one or more presentations.

We have developed PRIDE (Prediction In Dynamic Environments), a hierarchical multi-resolutional f... more We have developed PRIDE (Prediction In Dynamic Environments), a hierarchical multi-resolutional framework for moving object prediction that incorporates multiple prediction algorithms into a single, unifying framework. PRIDE incorporates two approaches for the prediction of the future location of moving objects at various levels of resolution at the frequency and level of abstraction necessary for planners at different levels within the hierarchy. These approaches, termed long-term (LT) and short-term (ST) predictions, respectively, are based on situation recognition and vehicle models for moving object prediction using sensor data. Our recent efforts have demonstrated the ability to use the results of the short-term prediction algorithms to strengthen/weaken the estimates of the long-term prediction algorithms. Based on previous experiments, we have found that the short-term prediction algorithms perform best when predicting on the order of a few seconds into the future and that the longer-term prediction algorithms are best at predicting on the order of several seconds into the future. In this paper, we explore the time window in which both the short-term and the long-term prediction algorithms provide reasonable results. Additionally, we describe a methodology by which we can determine the time point at which the short-term prediction algorithm no longer provides results within an acceptable predefined error threshold. We provide experimental results in an autonomous on-road driving scenario using AutoSim, a high-fidelity simulation tool that models details about road networks, including individual lanes, lane markings, intersections, legal intersection traversability, etc.

Proceedings of the 8th …, Jan 1, 2008

Internet stranica: http://www. mel. nist. …, Jan 1, 1997

Philadelphia, USA, Jan 1, 2004

Computational …, Jan 1, 2008

Chapter in the Climbing …, Jan 1, 2007

… 6081, National Institute of Standards and …, Jan 1, 1997