Erik S. Steinmetz

Model-based automation of the design of user interfaces to digital control systems

Digital control systems, like those controlling the functions of buildings or industrial processes, pose a number of special problems for good user interface design. The general problems of providing usability, common to all systems, include difficulty in accessing and applying principles of good design. In addition, digital control systems can have multiple users, with multiple roles, and each installation has different configurations of systems, controls, and user interface devices. Providing interactions for the users of building control systems is often achieved by manually implementing each required display. This is an expensive solution, which often produces less than optimal results. We address these problems through the automation of user interface design. Our solution, called DIGBE (dynamic interface generation for building environments), separates the domain knowledge, interaction design, and presentation heuristics into multiple collaborating models. Each model contains knowledge about a particular aspect of interface design, and uses this knowledge to dynamically create each user interface that is needed to support the users of a control system. DIGBE demonstrates that it is possible to automatically and dynamically create consistent and individualized user interfaces from model-based design knowledge.

Robot localization from landmarks using recursive total least squares

In the robot navigation problem, noisy sensor data must be filtered to obtain the best estimate of the robot position. We propose using a recursive total least squares algorithm to obtain estimates of the robot position. We avoid several weaknesses inherent in the use of the Kalman and extended Kalman filters, achieving much faster convergence without good initial (a priori) estimates of the position. The performance of the method is illustrated both by simulation and on an actual mobile robot with a camera.

Bid Evaluation and Selection in the MAGNET Automated Contracting System

We present an approach to the bid-evaluation problem in a system for multi-agent contract negotiation, called MAGNET. The MAGNET market infrastructure provides support for a variety of types of transactions, from simple buying and selling of goods and services to complex multi-agent contract negotiations. In the latter case, MAGNET is designed to negotiate contracts based on temporal and precedence constraints, and includes facilities for dealing with time-based contingencies. One responsibility of a customer agent in the MAGNET system is to select an optimal bid combination. We present an efficient anytime algorithm for a customer agent to select bids submitted by supplier agents in response to a call for bids. Bids might include combinations of subtasks and might include discounts for combinations. In an experimental study we explore the behavior of the algorithm based on the interactions of factors such as bid prices, number of bids, and number of subtasks. The results of experiments we present show that the algorithm is extremely efficient even for large number of bids.

Dynamic user interface adaptation based on operator role and task models

Proper design of human computer interactions currently requires the application of specialized knowledge possessed by talented individuals, often responding to rapidly changing technology and functionality. As computing power and data become more distributed, static design of interactions for dynamic environments may not always produce usable interfaces between people and machines. We have designed a model based, dynamic interaction design system called DIG (Dynamic Interaction Generation) and implemented it in a research prototype using the domain of digital building control systems. DIGBE is a three-tiered system modeling the domain data, the current interaction, and the device-specific presentation of the interaction. It responds to changes in the environment and creates, in real time, an interaction tailored to the current user role, access level, and task. Each interaction is also specialized to match the nature of the information that is currently the focus of the interaction. Full automatic synthesis of any interface at any time may not yet be feasible, but DIGBE demonstrates that it is both possible and useful to automatically generate user interfaces. This may be especially true for complex system domains with variable components but known task structures.

Recursive Total Least Squares: An Alternative to Using the Discrete Kalman Filter in Robot Navigation

In the robot navigation problem, noisy sensor data must be filtered to obtain the best estimate of the robot position. The discrete Kalman filter, commonly used for prediction and detection of signals in communication and control problems, has become a popular method to reduce the effect of uncertainty from the sensor data. However, in the domain of robot navigation, sensor readings are not only uncertain, but can also be relatively infrequent compared to traditional signal processing applications. In addition, a good initial estimate of location, critical for Kalman convergence, is often not available. Hence, there is a need for a filter that is capable of converging with a poor initial estimate and many fewer readings than the Kalman filter. To this end, we propose the use of a Recursive Total Least Squares Filter. This filter is easily updated to incorporate new sensor data, and in our experiments converged faster and to greater accuracy than the Kalman filter.

Implementation of automated interaction design with collaborative models

Abstract This paper summarizes the current status of an ongoing research program to explore automated alternatives to the current manual method of designing, implementing, and delivering user interfaces to complex digital control systems. Using examples from two implementations of the model-based interface automation approach that resulted from this research, we explore the models and collaboration required to perform on-demand user interface design. We first discuss the need for automation of the user interface design process and place the work into a research context. Using examples from two implemented systems, we then review the object-oriented models and processes that we used to support interaction design automation. Our findings support the application of model-based automated design approaches in digital control system domains, and particularly emphasize the need for rich semantic support for automated design.

DIGBE: ONLINE MODEL-BASED DESIGN AUTOMATION

We describe the results of a research and development program which led to the implementation of a model-based system which automatically generates user interfaces to digital control systems. This system, called DIGBE, is based on constraint-based collaboration between three models. DIGBE produces interfaces on demand; each detail of the interface is tailored to the user, the task, and the available data. The models in DIGBE include: a domain model, which builds a representation of the objects in the control system; an interaction model, which builds an abstract representation of the human-computer interaction; and a presentation model, which presents the interaction to the user on a particular hardware device such as a personal computer or a PDA.

Automated interaction design for command and control of military situations

We will demonstrate the SHARED software, which contains an implementation of the Automated Interaction Design (AID) approach to dynamic creation of user interfaces. AID uses multiple agents, multiple models, and productive compositional processes to generate need-based user interfaces within a complex control domain. In addition to demonstrating operational software that responds to military interaction needs, we will present details of the underlying models and operations that support user interface generation in this domain.