Hui-Min Huang

Autonomy Levels for Unmanned Systems (ALFUS) Framework: An Update

The initial construct of the framework for the Autonomy Levels of Unmanned Systems (ALFUS) was presented in the 2004 SPIE Defense and Security Symposium. This paper describes the continuing development effort and further accomplishments made by the Ad Hoc working group. We focus on two elements of the ALFUS product set, namely, the detailed model that is being implemented as a spreadsheet-based tool and the summary model. We also discuss identified challenges.

A feature-based inspection and machining system

Abstract This paper 1 describes an architecture for a system for machining and inspecting mechanical piece parts and an implementation of it called the Feature-Based Inspection and Control System (FBICS). In FBICS, the controller of a machining center or coordinate measuring machine uses a standard feature-based description of the shape of the object to be made as a principal input for machining and/or inspection. FBICS is a hierarchical control system and performs automated hierarchical process planning. FBICS serves: (1) to demonstrate feature-based inspection and control in an open-architecture control system; (2) as a testbed for solving problems in feature-based manufacturing; and (3) to test the usability of STEP methods and models.

Autonomy levels for unmanned systems (ALFUS) framework: safety and application issues

The Autonomy Levels for Unmanned Systems (ALFUS) framework is generic and applicable to multiple unmanned system (UMS) domains. The key component of the Framework is metrics along the three established axes or aspects. This paper attempts to examine how the metrics might be applied to selected domains that include homeland security, manufacturing, and defense. In particular, the paper attempts to lay out how the critical UMS concerns, including requirements specification, performance measures, safety, and risks might be established from the Framework.

AUTONOMY MEASURES FOR ROBOTS

Robots are becoming increasingly autonomous. Yet, there are no commonly accepted terms and measures of how “autonomous” a robot is. An ad hoc working group has been formed to address these deficiencies, focusing on the unmanned vehicles domain. This group is defining terminology relevant to unmanned systems and is devising metrics for autonomy levels of these systems. Autonomy definitions and measures must encompass many dimensions and serve many audiences. An Army general making decisions about deployment of unmanned scout vehicles may want to only know a value on a scale from 1 to 10, whereas test engineers need to know specifics about the types of environments and missions that the vehicles are expected to deal with. Any system will have to communicate with humans, hence this is an important dimension in evaluating autonomy. The autonomy levels for unmanned systems (ALFUS) group is therefore developing metrics based on three principal dimensions: task complexity, environmental difficulty, and human interaction. This paper reports on the current state of the ALFUS metric for evaluating robots.Copyright

A knowledge-based inspection workstation

We are building an inspection workstation development environment to use as a testbed for understanding what types of knowledge, e.g. data, algorithms and processes, can increase the productivity of inspection operations. Inspection can be more efficient through reducing the need for fixturing, integrating the generation of process plans and their execution within the controller, and reducing the errors or data losses that occur by translating the models to different formats. The initial configuration of inspection systems can be less costly through the use of open architectures that are constructed from components. Key elements of our work include in-situ feature-based planning, vision-driven part pose estimation and software methods to facilitate construction of manufacturing controllers. These provide a rich environment in which to study the categories of knowledge that are useful in intelligent control of inspection workstations. This paper describes our vision, approach and preliminary results.

Precise Definition of Software Component Specifications

Abstract A set of generic specification categories is presented which can be used to comprehensively define any software component within a certain class. With these categories as a template, a specific set of formal specifications can be generated for each component. Specifications for a particular component (an algorithm that estimates the position and orientation of a physical object using visual sensing) have been defined in EXPRESS, an information modeling language. A few example natural language specifications are presented for this particular component.

A submarine maneuvering system demonstration based on the NIST real-time control system reference model

The Robot Systems Division (RSD) at the National Institute of Standards and Technology (NIST) has developed a generic reference model architecture, known as the Real-time Control System (RCS). The application of RCS to the automation of submarine operations is demonstrated which requires that an enormous amount of intelligence be built into its control system. A summary of the reference model is given, followed by a description of the implementation process. The long term goal is to establish a generic development methodology for intelligent control systems.<<ETX>>

Comprehensive standard test suites for the performance evaluation of mobile robots

Robots must possess certain sets of capabilities to suit critical operations such as emergency responses. In the mobility function, ground robots must be able to handle many types of obstacles and terrain complexities, including traversing and negotiating positive and negative obstacles, various types of floor surfaces or terrains, and confined passageways. Additional mobility requirements include the ability to sustain specified speeds and to tow payloads with different weights. Standard test methods are required to evaluate how well candidate robots meet these requirements. A set of test methods focused on evaluating the mobility function has been collected into a test suite. Likewise, in other functions such as sensing, communication, manipulation, energy/power, Human-System Interaction (HSI), logistics, and safety, corresponding test suites are required. Also needed are test suites for aerial and aquatic robots. Under the sponsorship of DHS, NIST researchers are collaborating with others to establish such a collection of test suites under the standards development organization ASTM International. Apparatuses must be set up to challenge specific robot capabilities in repeatable ways to facilitate direct comparison of different robot models as well as particular configurations of similar robot models.

Specifying autonomy levels for unmanned systems: interim report

The viability of Unmanned Systems as tools is increasingly recognized in many domains. As technology advances, the autonomy on board these systems also advances. In order to evaluate the systems in terms of their levels of autonomy, it is critical to have a set of standard definitions that support a set of metrics. As autonomy cannot be evaluated quantitatively without sound and thorough technical basis, the development of autonomy levels for unmanned systems must take into account many factors such as task complexity, human interaction, and environmental difficulty. An ad hoc working group assembled by government practitioners has been formed to address these issues. The ultimate objectives for the working group are: (1) To determine the requirements for metrics for autonomy levels of unmanned systems. (2) To devise methods for establishing metrics of autonomy for unmanned systems. (3) To develop a set of widely recognized standard definitions for the levels of autonomy for unmanned systems. This paper describes the interim results that the group has accomplished through the first four workshops that the group held. We report on the initial findings of the workshops toward developing a generic framework for the Autonomy Levels for Unmanned Systems (ALFUS).

Characterizing Unmanned System Autonomy:Contextual Autonomous Capability and Level of Autonomy Analyses

The Autonomy Levels for Unmanned Systems (ALFUS) workshop series was convened to address the autonomous nature of unmanned, robotic systems, or unmanned systems (UMS). Practitioners have different perceptions or different expectations for these systems. The requirements on human interactions, the types of tasks, the teaming of the UMSs and the humans, and the operating environment are just a few of the issues that need to be clarified. Also needed is a set of definitions and a model with which the autonomous capability of the UMS can be described. This paper reports the current results and status of the ALFUS framework, which practitioners can apply to analyze the autonomy requirements and to evaluate the performance of their robotic programs.