MissionLab is a mission specification system that implements a hybrid deliberative and reactive control architecture for autonomous mobile robots. The user creates and executes the robot mission plans through its graphical user interface. As robot deployments become more common in highly stressful situations, such as in dealing with explosives or biohazards, the usability of their mission specification system becomes critical. To address this need, a mission-planning "wizard" has been recently integrated into MissionLab. By retrieving and adapting past successful mission plans stored in its database, this new feature is designed to simplify the user's planning process. The latest formal usability experiments, reported in this paper, testing for usability improvements in terms of speed of the mission planning process, accuracy of the produced mission plans, and ease of use is conducted. This paper introduces the mission-planning wizard, describes the usability experiments (including design), and discusses the results in detail.

The PackBots being used by the U.S. military in Afghanistan and the urban search and rescue (USAR) robots that worked the World Trade Center site are just two recent examples of mobile robots moving from the laboratory to the field. What is significant about these new applications is that they invariably involve some form of human-robot interaction (HRI) rather than the full robot autonomy that has motivated most prior research. Conducting HRI research can be extremely difficult because experimentation with physical robots is expensive and time consuming. Few roboticists have experience or interest in conducting human experimentation while researchers in human factors or human computer interaction often lack experience in programming robots or access to robotic platforms. In this paper we describe a high fidelity open source simulation intended for HRI researchers of varying backgrounds and providing reference tasks and environments to facilitate collaboration and sharing of results. The architecture and capabilities of the game engine-based USARSim simulation are described. Its use for HRI research is illustrated through case studies describing experiments in camera control for remote viewing and integrated display of attitude information.

Abstract — A software toolset for the design of robots is described. Modular and system level design issues are discussed and criteria for the appropriate selection of software design tools are presented. Case studies of a design toolset illustrate the principles. I.

Abstract—Robot swarms are capable of performing tasks with robustness and flexibility using only local interactions between the agents. Such a system can lead to emergent behavior that is often desirable, but difficult to control and manipulate postdesign. These properties make the real-time control of swarms by a human operator challenging—a problem that has not been adequately addressed in the literature. In this paper we present preliminary work on two possible forms of control: top-down control of global swarm characteristics and bottom-up control by influencing a subset of the swarm members. We present learning methods to address each of these. The first method uses instance-based learning to produce a generalized model from a sampling of the parameter space and global characteristics for specific situations. The second method uses evolutionary learning to learn placement and parameterization of virtual agents that can influence the robots in the swarm. Finally we show how these methods generalize and can be used by a human operator to dynamically control a swarm in real time. I.

Abstract—There is considerable interest in real-world formation-maintenance tasks, where robots move together while maintaining a geometric shape. This interest is motivated by promise of robustly and efficiently moving multiple robots along a path, guided by a human operator. This paper presents a comprehensive set of techniques that fulfill this promise: (i) a novel method for fusing open- and closed- loop controllers, for robust formation-maintenance; (ii) an ecological display, allowing a human operator to monitor and guide robots, while improving their performance and reducing the failure rate; and (iii) a set of methods for interacting with the formation in the case of a disconnect in the formation. We evaluate each of these contributions in extensive experiments, including 25 human operators. We show significant improvements in performance (in terms of movement time), robustness (both in number of failures, as well as failure rate), and consistency between operators. I.

ABSTRACT: The PackBots being used by the U.S. military in Afghanistan and the urban search and rescue (USAR) robots that worked the World Trade Center site are just two recent examples of mobile robots moving from the laboratory to the field. What is significant about these new applications is that they invariably involve some form of human-robot interaction (HRI) rather than the full robot autonomy that has motivated most prior research. Conducting HRI research can be extremely difficult because experimentation with physical robots is expensive and time consuming. Few roboticists have experience or interest in conducting human experimentation, and researchers in human factors or human-computer interaction often lack experience in programming robots or access to robotic platforms. In this paper, we describe a high-fidelity, open-source simulation intended for HRI researchers of varying backgrounds and provide reference tasks and environments to facilitate collaboration in order to share the results. The architecture and capabilities of the game engine–based USARSim simulation are described. Its use for HRI research is illustrated through case studies describing experiments in camera control for remote viewing and integrated display of attitude information.

In this article a new approach of designing multiagent Internet telerobotic systems is described. The architectural innovation includes two interfaces, either of them lays between Human Interactive Computers (HICs) and the Task Interactive Computer (TIC), which provides supervisory control services required by a particular multiagent Internet telerobot systems, the other provides agent interconnect services.

There is growing recognition that many applications of robots will require a human operator to supervise and control multiple robots that collaborate to achieve the operator’s goals. However, the bulk of existing work in this area assumes that robots are independent of each other, and thus ignores key challenges and opportunities in monitoring and operating tightly-coordinating teams. This thesis takes steps to address these open issues. First, we address the challenge of effectively monitoring multiple coordinating robots. We introduce a graphical socially-attentive display that explicitly shows the state of coordination in the team, in terms of the robots ’ state with respect to each other. As a result, the operator can easily detect coordination failures, even before these cause overall failure in the task. Second, we show that in resolving contingencies (callrequests), an opportunity exists for taking advantage of the robots ’ teamwork, to allow the robots to actively assist the operator. We propose a distributed approach to call-request resolution (including two variations), and an implementation method for behavior-based robots. This implementation method allows the