Craig I. Schlenoff

A robot ontology for urban search and rescue

The goal of this Robot Ontology effort is to develop and begin to populate a neutral knowledge representation (the data structures) capturing relevant information about robots and their capabilities to assist in the development, testing, and certification of effective technologies for sensing, mobility, navigation, planning, integration and operator interaction within search and rescue robot systems. This knowledge representation must be flexible enough to adapt as the robot requirements evolve. As such, we have chosen to use an ontological approach to representing these requirements. This paper describes the Robot Ontology, how it fits in to the overall Urban Search and Rescue effort, how we will be proceeding in the future.

An IEEE standard Ontology for Robotics and Automation

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. The standard provides a unified way of representing knowledge and provides a common set of terms and definitions, allowing for unambiguous knowledge transfer among any group of humans, robots, and other artificial systems. In addition to describing the goal and structure of the group, this article gives some examples of how the ontology, once developed, can be used by applications such as industrial kitting.

Ontology-based methods for enhancing autonomous vehicle path planning

Abstract We report the results of a first implementation demonstrating the use of an ontology to support reasoning about obstacles to improve the capabilities and performance of on-board route planning for autonomous vehicles. This is part of an overall effort to evaluate the performance of ontologies in different components of an autonomous vehicle within the 4D/RCS system architecture developed at NIST. Our initial focus has been on simple roadway driving scenarios where the controlled vehicle encounters potential obstacles in its path. As reported elsewhere [C. Schlenoff, S. Balakirsky, M. Uschold, R. Provine, S. Smith, Using ontologies to aid navigation planning in autonomous vehicles, Knowledge Engineering Review 18 (3) (2004) 243–255], our approach is to develop an ontology of objects in the environment, in conjunction with rules for estimating the damage that would be incurred by collisions with different objects in different situations. Automated reasoning is used to estimate collision damage; this information is fed to the route planner to help it decide whether to plan to avoid the object. We describe the results of the first implementation that integrates the ontology, the reasoner and the planner. We describe our insights and lessons learned and discuss resulting changes to our approach.

An Analysis of Existing Ontological Systems for Applications in Manufacturing and Healthcare

The objective of the work described in this paper is to move closer to the ultimate goal of seamless system integration using the principle behind ontological engineering to unambiguously define domain-specific concepts. A major challenge facing industry today is the lack of interoperability between heterogeneous systems. This challenge is apparent in many sectors, including both healthcare and manufacturing. Current integration efforts are usually based solely on how information is represented (the syntax) without a description of what the information means (the semantics). With the growing complexity of information and the increasing need to completely and correctly exchange information among different systems, the need for precise and unambiguous capture of the meaning of concepts within a given system is becoming apparent.

An industrial robotic knowledge representation for kit building applications

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. This is a process that brings parts that will be used in assembly operations together in a kit and then moves the kit to the assembly area where the parts are used in the final assembly. This paper examines the knowledge representations that have been developed and implemented for the kitting problem.

How task analysis can be used to derive and organize the knowledge for the control of autonomous vehicles

Abstract The real-time control system (RCS) methodology has evolved over a number of years as a technique to capture task knowledge and organize it in a framework conducive to implementation in computer control systems. The fundamental premise of this methodology is that the present state of the task activities sets the context that identifies the requirements for all the support processing. In particular, the task context at any time determines what is to be sensed in the world, what world model states are to be evaluated, which situations are to be analyzed, what plans should be invoked, and which behavior generation knowledge is to be accessed. This results in a methodology that concentrates first and foremost on the task definition. It starts with the definition of the task knowledge in the form of a decision tree that clearly represents the branching of tasks into layers of simpler and simpler subtask sequences. This task decomposition framework is then used to guide the search for and to emplace all of the additional knowledge. This paper explores this process in some detail, showing how this knowledge is represented in a task context-sensitive relationship that supports the very complex real-time processing the computer control systems will have to do.

Using ontologies to aid navigation planning in autonomous vehicles

This paper explores the hypothesis that ontologies can be used to improve the capabilities and performance of on-board route planning for autonomous vehicles. We name a variety of general benefits that ontologies may provide, and list numerous specific ways that ontologies may be used in different components of our chosen infrastructure: the 4D/RCS system architecture developed at NIST. Our initial focus is on simple roadway driving scenarios where the controlled vehicle encounters objects in its path. Our approach is to develop an ontology of objects in the environment, in conjunction with rules for estimating the damage that would be incurred by collisions with the different objects in different situations. Automated reasoning is used to estimate collision damage; this information is fed to the route planner to help it decide whether to avoid the object. We describe our current experiments and plans for future work.

Evaluating speech translation systems: applying SCORE to TRANSTAC technologies

The Spoken Language Communication and Translation System for Tactical Use (TRANSTAC) program is a Defense Advanced Research Projects Agency (DARPA) advanced technology research and development program. The goal of the TRANSTAC program is to demonstrate capabilities to rapidly develop and field free-form, two-way translation systems that enable speakers of different languages to communicate with one another in realworld tactical situations without an interpreter. The National Institute of Standards and Technology (NIST), along with support from MITRE and Appen Pty Ltd., have been funded to serve as the Independent Evaluation Team (IET) for the TRANSTAC Program. The IET is responsible for analyzing the performance of the TRANSTAC systems by designing and executing multiple TRANSTAC evaluations and analyzing the results of the evaluation. To accomplish this, NIST has applied the SCORE (System, Component, and Operationally Relevant Evaluations) Framework. SCORE is a unified set of criteria and software tools for defining a performance evaluation approach for complex intelligent systems. It provides a comprehensive evaluation blueprint that assesses the technical performance of a system and its components through isolating variables as well as capturing end-user utility of the system in realistic use-case environments. This document describes the TRANSTAC program and explains how the SCORE framework was applied to assess the technical and utility performance of the TRANSTAC systems.

Moving Object Prediction for Off-road Autonomous Navigation

The realization of on- and off-road autonomous navigation of Unmanned Ground Vehicles (UGVs) requires real-time motion planning in the presence of dynamic objects with unknown trajectories. To successfully plan paths and to navigate in an unstructured environment, the UGVs should have the difficult and computationally intensive competency to predict the future locations of moving objects that could interfere with its path. This paper details the development of a combined probabilistic object classification and estimation theoretic framework to predict the future location of moving objects, along with an associated uncertainty measure. The development of a moving object testbed that facilitates the testing of different representations and prediction algorithms in an implementation-independent platform is also outlined.

Evolution of the SCORE framework to enhance field-based performance evaluations of emerging technologies

NIST has developed the System, Component, and Operationally-Relevant Evaluations (SCORE) framework as a formal guide for designing evaluations of emerging technologies. SCORE captures both technical performance and end-user utility assessments of systems and their components within controlled and realistic environments. Its purpose is to present an extensive (but not necessarily exhaustive) picture of how a system would behave in a realistic operating environment. The framework has been applied to numerous evaluation efforts over the past three years producing valuable quantitative and qualitative metrics. This paper will present the building blocks of the SCORE methodology including the system goals and design criteria that drive the evaluation design process. An evolution of the SCORE framework in capturing utility assessments at the capability level of a system will also be presented. Examples will be shown of SCOREs successful application to the evaluation of the soldier-worn sensor systems and two-way, free-form spoken language translation technologies.