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The use of robots, especially autonomous mobile robots, to support work is expected to increase over the next few decades. However, little empirical research examines how users form mental models of robots, how they collaborate with them, and what factors contribute to the success or failure of human-robot collaboration. A two-year observational study of a collaborative human-robot system suggests that the factors disrupting the creation of common ground for interactive communication change at different levels of robot autonomy. Our observations of users collaborating with the remote robot showed differences in how the users reached common ground with the robot in terms of an accurate, shared understanding of the robot's context, planning, and actions - a process called grounding. We focus on how the types and levels of robot autonomy affect grounding. We also examine the challenges a highly autonomous system presents to people's ability to maintain a shared mental model of the robot

This paper describes the latest advances made to a software architecture designed to control multiple miniature robots. As the robots themselves have very limited computational capabilities, a distributed control system is needed to coordinate tasks among a large number of robots. Two of the major challenges facing such a system are the scheduling of access to system resources and the distribution of work across multiple workstations. This paper discusses solutions to these problems in the context of a distributed surveillance task.

Reduced cost of robotic hardware enables the use of teams of robots instead of a single device. Multi-robot approaches promise faster results and more robust systems as each individual robot becomes dispensable. Given higher numbers of robots, writing dependable control software becomes more complex and thus more expensive. Consequently, a software architecture that is readily applied to new missions becomes essential. In the following, an architecture for distributed control of a team of heterogeneous mobile robots is introduced. Design as well as implementation details are presented. A distinguishing feature of the architecture is its versatility in handling resources. An example application for a surveillance task is discussed.

While a large number of robotics programs for K-12 students have been developed and deployed in the past twenty years, the effect that these programs have on students' motivations to enter science, technology, engineering, and mathematics (STEM) careers has yet to be fully determined. In order to demonstrate the value of these programs, researchers must make a concerted effort to measure their impact. Based on prior work in the evaluation of educational robotics programs, the authors of this chapter present frequently-utilized evaluation and measurement methods as well as guidelines for selecting these methods based on factors such as a program's duration, size, and maturity. This chapter is intended for use as a reference guide for designing evaluations of K-12 educational robotics programs.

In this paper, we present a user study of a new collaborative communication method between a user and remotely-located robot performing an exploration task. In the studied scenario, our user possesses scientific expertise but not necessarily detailed knowledge of the robot's capabilities, resulting in very little common ground between the user and robot. Because the robot is not available during mission planning, we introduce a robot proxy to build common ground with the user. Our robot proxy has the ability to provide feedback to the user about the user's plans before the plans are executed. Our study demonstrated that the use of the robot proxy resulted in improved performance and efficiency on an exploration task, more accurate mental models of the robot's capabilities, a stronger perception of effectiveness at the task, and stronger feelings of collaboration with the robotic system.

A daylight fluorescence imager was deployed on an autonomous rover, Zoe, to detect life on the surface and shallow subsurface in regions of the Atacama Desert in Chile during field tests between 2003 and 2005. In situ fluorescent measurements were acquired from naturally fluorescing biomolecules such as chlorophyll and from specific fluorescent probes sprayed on the samples, targeting each of the four biological macromolecule classes: DNA, protein, lipid, and carbohydrate. RGB context images were also acquired. Preparatory reagents were applied to enhance the dye probe penetration and fluorescence intensity of chlorophyll. Fluorescence imager data sets from 257 samples were returned to the Life in the Atacama science team. A variety of visible life forms, such as lichens, were detected, and several of the dye probes produced signals from nonphotosynthetic microorganisms.

[1] The science goals of the Life in the Atacama (LITA) robotic field experiment are to understand habitat and seek out life in the Atacama Desert, Chile, as an analog to future missions to Mars. To those ends, we present a new data analysis tool, the LITA Data Scoring System (DSS), which (1) integrates rover and orbital data relevant to environmental habitability and life detection, and (2) provides a standard metric, or “score” to evaluate (a) the potential habitability, and (b) the strength of evidence for life at all locales along the rover's traverse. Designed and tested during the 2005 field campaign, first results from the DSS indicate that the three selected sites in the Atacama Desert are generally inhospitable. The strength of evidence for life is positively correlated with potential habitability at two of the three sites. Using factor analysis, we find three factors explain 79.9% of the variance in biological observations and five factors explain 96.2% of the variance in potential habitability across all sites. These factors are used to focus a discussion of scoring variable definitions for future robotic missions in the Atacama and of instrument selection and strategy development for future robotic missions on Earth and Mars.

[1] The Life in the Atacama project examined six different sites in the Atacama Desert (Chile) over 3 years in an attempt to remotely detect the presence of life with a rover. The remote science team, using only orbital and rover data sets, identified areas with a high potential for life as targets for further inspection by the rover. Orbital data in the visible/near infrared (VNIR) and in the thermal infrared (TIR) were used to examine the mineralogy, geomorphology, and chlorophyll potential of the field sites. Field instruments included two spectrometers (VNIR reflectance and TIR emission) and a neutron detector: this project represents the first time a neutron detector has been used as part of a “science-blind” rover field test. Rover-based spectroscopy was used to identify the composition of small scale features not visible in the orbital images and to improve interpretations of those data sets. The orbital and ground-based data sets produced consistent results, suggesting that much of the field sites consist of altered volcanic terrains with later deposits of sulfates, quartz, and iron oxides. At one location (Site A), the ground-based spectral data revealed considerably greater compositional diversity than was seen from the orbital view. One neutron detector transect provided insight into subsurface hydrogen concentrations, which correlated with life and surface features. The results presented here have implications for targeting strategies, especially for future Mars rover missions looking for potential habitats/paleohabitats.

[1] As part of the three-year ‘Life in the Atacama’ (LITA) project, plant and microbial abundance were mapped within three sites in the Atacama Desert, Chile, using an automated robotic rover. On-board fluorescence imaging of six biological signatures (e.g., chlorophyll, DNA, proteins) was used to assess abundance, based on a percent positive sample rating system and standardized robotic ecological transects. The percent positive rating system scored each sample based on the measured signal strength (0 for no signal to 2 for strong signal) for each biological signature relative to the total rating possible. The 2005 field experiment results show that percent positive ratings varied significantly across Site D (coastal site with fog), with patchy zones of high abundance correlated with orbital and microscale habitat types (heaved surface crust and gravel bars); alluvial fan habitats generally had lower abundance. Non-random multi-scale biological patchiness also characterized interior desert Sites E and F, with relatively high abundance associated with (paleo)aqueous habitats such as playas. Localized variables, including topography, played an important, albeit complex, role in microbial spatial distribution. Site D biosignature trends correlated with culturable soil bacteria, with MPN ranging from 10-1000 CFU/g-soil, and chlorophyll ratings accurately mapped lichen/moss abundance (Site D) and higher plant (Site F) distributions. Climate also affected biological patchiness, with significant correlation shown between abundance and (rover) air relative humidity, while lichen patterns were linked to the presence of fog. Rover biological mapping results across sites parallel longitudinal W-E wet/dry/wet Atacama climate trends. Overall, the study highlights the success of targeting of aqueousassociated habitats identifiable from orbital geology and mineralogy. The LITA experience also suggests the terrestrial study of life and its distribution, particularly the fields of landscape ecology and ecohydrology, hold critical lessons for the search for life on other planets. Their applications to robotic sampling strategies on Mars should be further exploited.

[1] The Life in the Atacama project investigated the regional distribution of life and habitats in the Atacama Desert of Chile. We sought to create biogeologic maps through survey traverses across the desert using a rover carrying biologic and geologic instruments. Elements of our science approach were to: Perform ecological transects from the relatively wet coastal range to the arid core of the desert; use converging evidence from science instruments to reach conclusions about microbial abundance; and develop and test exploration strategies adapted to the search of scattered surface and shallow subsurface microbial oases. Understanding the ability of science teams to detect and characterize microbial life signatures remotely using a rover became central to the project. Traverses were accomplished using an autonomous rover in a method that is technologically relevant to Mars exploration. We present an overview of the results of the 2003, 2004, and 2005 field investigations. They include: The confirmed identification of microbial habitats in daylight by detecting fluorescence signals from chlorophyll and dye probes; the characterization of geology by imaging and spectral measurement; the mapping of life along transects; the characterization of environmental conditions; the development of mapping techniques including homogeneous biological scoring and predictive models of habitat location; the development of exploration strategies adapted to the search for life with an autonomous rover capable of up to 10 km of daily traverse; and the autonomous detection of life by the rover as it interprets observations on-the-fly and decides which targets to pursue with further analysis.

[1] The Atacama Desert, one of the most arid landscapes on Earth, serves as an analog for the dry conditions on Mars and as a test bed in the search for life on other planets. During the Life in the Atacama (LITA) 2004 field experiment, satellite imagery and ground-based rover data were used in concert with a ‘follow-the-water’ exploration strategy to target regions of biological interest in two (1 coastal, 1 inland) desert study sites. Within these regions, environments were located, studied and mapped with spectroscopic and fluorescence imaging (FI) for habitats and microbial life. Habitats included aqueous sedimentary deposits (e.g., evaporites), igneous materials (e.g., basalt, ash deposits), rock outcrops, drainage channels and basins, and alluvial fans. Positive biological signatures (chlorophyll, DNA, protein) were detected at 81% of the 21 locales surveyed with the FI during the long-range, autonomous traverses totaling 30 km. FI sensitivity in detecting microbial life in extreme deserts explains the high percentage of positives despite the low actual abundance of heterotrophic soil bacteria in coastal (

To help answer questions about the behavior of participants in human-robot systems, we propose the Cognitive Evaluation of Human-Robot Systems (CEHRS) method based on our work with the Personal Exploration Rover (PER). The CEHRS method consists of six steps: (1) identify all system participants, (2) collect data from all participant groups, including the system?s creators, (3) analyze participant data in light of system-wide goals, (4) answer targeted questions about each participant group to determine the flow of knowledge, information, and influence throughout the system, (5) look for inconsistencies in the knowledge and beliefs of different participant groups, and (6) make recommendations for improvement. We offer this comprehensive, human-centered evaluation method as a starting point for future work in understanding cognitive change in human-robot interactions.

We report a study of a human-robot system composed of a science team (located in Pittsburgh), an engineering team (located in Chile), and a robot (located in Chile). We performed ethnographic observations simultaneously at both sites over two weeks as scientists collected data using the robot. Our data reveal problems in establishing and maintaining common ground between the science team and the robot due to missing contextual information about the robot. Our results have implications for the design of systems to support human-robot interaction.

When designing a mobile robotic team, an engineer is faced with many design choices. This paper discusses the design of a team consisting of two different models of robots with significantly different sensing and control capabilities intended to accomplish a similar task. Two new robotic platforms, the COTS Scout and the MegaScout are described along with their respective design considerations.

This paper presents the design and testing of Kana Warrior, a new interface for basic Japanese character recognition based on a game-style user interface. Kana Warrior is a game designed to help Japanese students learn to read characters quickly. A small pilot study has been conducted with very encouraging results. These results support the idea that game-style interfaces may be of benefit to users outside of the realm of entertainment programs.

Robotic reconnaissance and search and rescue are daunting tasks, especially in unknown and dynamic environments. The Scout is a robotic platform that is robust and flexible to operate in adverse and changing situations without revealing itself or disturbing the environment. The Scout can complete these missions by utilizing its small form factor for effective deployment, placement, and concealment while being equipped with a variety of sensors to accommodate different objectives. Unfortunately, the Scout has a limited volume to share among power, locomotion, sensors, and communications. Several novel approaches addressing deficiencies in specific tasks have been implemented in specialized Scouts and will be discussed in this paper. By building a diverse team of specialized Scouts, the team’s strengths outweigh an individual weakness.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University’s Department of Computer Science, is pleased to present the 2010 Spring Symposium Series, to be held Monday through Wednesday, March 22–24, 2010 at Stanford University. The titles of the seven symposia are Artificial Intelligence for Development; Cognitive Shape Processing; Educational Robotics and Beyond: Design and Evaluation; Embedded Reasoning: Intelligence in Embedded Systems Intelligent Information Privacy Management; It’s All in the Timing: Representing and Reasoning about Time in Interactive Behavior; and Linked Data Meets Artificial Intelligence.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, was pleased to present the 2009 Spring Symposium Series, held Monday through Wednesday, March 23–25, 2009 at Stanford University. The titles of the nine symposia were Agents that Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning Systems, Experimental Design for Real-World Systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents that Learn from Human Teachers was to investigate how we can enable software and robotics agents to learn from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning Systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The Experimental Design symposium discussed the challenges of evaluating AI systems. The Human Behavior Modeling symposium explored reasoning methods for understanding various aspects of human behavior, especially in the context of designing intelligent systems that interact with humans. The Intelligent Event Processing symposium discussed the need for more AI-based approaches in event processing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies II AAAI symposium discussed innovations, progress, and novel techniques in the research domain. The Learning by Reading and Learning to Read symposium explored two aspects of making natural language texts semantically accessible to, and processable by, machines. The Social Semantic Web symposium focused on the real-world grand challenges in this area. Finally, the Technosocial Predictive Analytics symposium explored new methods for anticipatory analytical thinking that provide decision advantage through the integration of human and physical models.