Abstract—Multi-robot remote driving has traditionally been a difficult problem. Whenever an operator is forced to divide his limited resources (attention, cognition, etc.) among multiple robots, control becomes complicated and performance deteriorates as a result. Thus, we need to find ways to make command generation and coordination efficient, so that human–robot interaction becomes transparent and tasks are easy to perform. In this paper, we discuss how human–robot collaboration and dialogue provide an effective framework for achieving this. Index Terms—Collaborative control, human–robot interaction, mobile robots, remote driving, vehicle teleoperation.

13.44> . Drew Kessler for help with the SVE toolkit . The Virtual Environments group at Georgia Tech . The numerous experimental subjects who volunteered their time . Dawn Bowman iv TABLE OF CONTENTS Introduction ..................................................................... ................. 1 1.1 Motivation ..................................................................... ...............1 1.2 Definitions.......................................................... ..........................4 1.3 Problem Statement............................................................ ...............6 1.4 Scope of the Research............................................................. ..........7 1.5 Hypotheses........................................................... ........................8 1.6 Contributions........................................................ .....

Telerobotic systems have traditionally been designed and operated from a human point of view. Though this approach suffices for some domains, it is clearly sub-optimal for tasks such as operating multiple vehicles or controlling planetary rovers. Thus, I believe it is worthwhile to examine a new teleoperation approach: collaborative control. In this robot-centric model, instead of the human always being "in charge", the robot works as a peer and makes requests of the human. In other words, the human is treated as an imprecise, limited source of planning and information, just like sensors and maps and other noisy modules. To examine the numerous human-machine interaction and system design issues raised by this new approach, I propose to build a vehicle teleoperation system based on collaborative control. In my research, I will show how this approach enables efficient teleoperation and optimizes use of human resources.

Human-computer interaction (HCI) is the study of how people design, implement, and use interactive computer systems and how computers affect individuals, organizations, and society. This encompasses not only ease of use but also new interaction techniques for supporting user tasks, providing better access to information, and creating more powerful forms of communication. It involves input and output devices and the interaction techniques that use them; how information is presented and requested; how the computer’s actions are controlled and monitored; all forms of help, documentation, and training; the tools used to design, build, test, and evaluate user interfaces; and the processes that developers follow when creating interfaces. This report describes the historical and intellectual foundations of HCI and then summarizes selected strategic directions in human-computer interaction research. Previous important reports on HCI directions include the results of the

As the application of computer technology continues to proliferate and diversify, the identification and understanding of application domains is becoming increasingly important to software development methodologies. Domain analysis techniques have been developed to accumulate and formalize the knowledge necessary for successful software reuse. These techniques have been shown to be useful, but suffer from defining the domain too restrictively, burying important relationships deep in domain taxonomies, and prohibiting flexible identification of domains with common issues. Techniques are needed that dynamically detect recurring patterns of activities in development projects. This paper presents a method for developing and refining the knowledge and experience accumulated by a development organization so it can learn from previous efforts. A case-based repository of project experiences supports the re-use and refinement of domain knowledge to reduce duplicate effort, build on successful e...

Modern software development is a knowledge-intensive activity. The proliferation of development tools, rapidly changing technology, and increasing complexity and diversity of application domains all increase the cognitive burden placed on software developers. General purpose programming languages and CASE tools offer little relief from these problems. Knowledge management tools are needed that can effectively capture and disseminate software development knowledge that applies to the domain-specific needs of an organization. This knowledge is not static, but evolves with technology and the changing needs of the organization's development practices, customer base, and business milieu.

Work system analysis and design is complex and nondeterministic. In this paper we describe Brahms, a multiagent modeling and simulation environment for designing complex interactions in human--machine systems. Brahms was originally conceived as a business process design tool that simulates work practices, including social systems of work. We describe our modeling and simulation method for mission operations work systems design, based on a research case study in which we used Brahms to design mission operations for a proposed discovery mission to the Moon. We then describe the results of an actual method application project---the Brahms Mars Exploration Rover. Space mission operations are similar to operations of traditional organizations; we show that the application of Brahms for space mission operations design is relevant and transferable to other types of business processes in organizations.

We have developed a new teleoperation system model called collaborative control. With this model, the robot asks the human questions, to obtain assistance with cognition and perception during task execution. This enables the human to support the robot and to compensate for inadequacies in autonomy. In the following, we review the system models conventionally used in teleoperation, describe collaborative control, and discuss its use.

Abstract. Change awareness is the ability of individuals to track the asynchronous changes made to a collaborative document or surface by other participants over time. We develop a framework that articulates what change awareness information is critical if people are to track and maintain change awareness. Information elements include: knowing who changed the artifact, what those changes involve, where changes occur, when changes were made, how things have changed, and why people made the changes. The framework also accounts for people’s need to view these changes from different perspectives: an artifactbased view, a person-based view, and a workspace-based view. 1

Collaborative control is a teleoperation system model based on human-robot dialogue. With this model, the robot asks questions to the human in order to obtain assistance with cognition and perception. This enables the human to function as a resource for the robot and to help compensate for limitations of autonomy. To understand how collaborative control influences human-robot interaction, we performed a user study based on contextual inquiry. The study revealed that: (1) dialogue helps users understand problems encountered by the robot and (2) human assistance is a limited resource that must be carefully managed.