Autonomy and Common Ground in Human-Robot Interaction: A Field Study

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     

Optimizing Information Value: Improving Rover Sensor Data Collection

Robotic exploration is an excellent method for obtaining information about sites too dangerous for people to explore. The operator's understanding of the environment depends on the rover returning useful information. Robotic mission bandwidth is frequently constrained, limiting the amount of information the rover can return. This paper explores the tradeoff between information and bandwidth based on two years of observations during a robotic astrobiology field study. The developed theory begins by analyzing the search task conducted by robot operators. This analysis leads to an information optimization model. Important parameters in the model include the value associated with detecting a target, the probability of locating a target, and the bandwidth required to collect the information from the environment. Optimizing the information return between regions creates an image and provides the necessary information while reducing bandwidth. Application of the model to the analyzed field study results in an optimized image that requires 48.3% less bandwidth to collect. The model also predicts several data collection patterns that could serve as the basis of data collection templates for improving mission effectiveness. The developed optimization model reduces the bandwidth necessary to collect information, thus aiding missions in collecting more information from the environment.     

Autonomous science during large‐scale robotic survey

Today's planetary exploration robots rarely travel beyond the yesterday imagery. However, advances in autonomous mobility will soon permit single‐command site surveys of multiple kilometers. Here scientists cannot see the terrain in advance, and explorer robots must navigate and collect data autonomously. Onboard science data understanding can improve these surveys with image analysis, pattern recognition, learned classification, and information‐theoretic planning. We report on field experiments near Amboy Crater, California, that demonstrate fundamental capabilities for autonomous surficial mapping of geologic phenomena with a visible near‐infrared spectrometer. We develop an approach to “science on the fly'' that adapts the robot's exploration using collected instrument data. We demonstrate feature detection and visual servoing to acquire spectra from dozens of targets without human intervention. The rover interprets spectra onboard, learning spatial models of science phenomena that guide it toward informative areas. It discovers spatial structure (correlations between neighboring regions) and cross‐sensor structure (correlations between different scales). The rover uses surface observations to reinterpret satellite imagery and improve exploration efficiency. © 2011 Wiley Periodicals, Inc.     

Creation of a unit block library of architectures for use in assembled scaffold engineering

Guided tissue regeneration is gaining importance in the field of orthopaedic tissue engineering as need and technology permits the development of site-specific engineering approaches. Computer Aided Design (CAD) and Finite Element Analysis (FEA) hybridized with manufacturing techniques such as Solid Freeform Fabrication (SFF), is hypothesized to allow for virtual design, characterization, and production of scaffolds optimized for tissue replacement. However, a design scope this broad is not often realized due to limitations in preparing scaffolds both for biological functionality and mechanical longevity. To aid scientists in fabrication of a successful scaffold, we propose characterization and documentation of a library of micro-architectures, capable of being seamlessly merged according to the mechanical properties (stiffness, strength), flow perfusion characteristics, and porosity, determined by the scientist based on application and anatomic location. The methodology is discussed in the sphere of bone regeneration, and examples of catalogued shapes are presented. Similar principles may apply for other organs as well.     

Exploring Mount Erebus by walking robot

Dante is a tethered walking robot capable of climbing steep slopes. In 1992 it was created at Carnegie Mellon University and deployed in Antarctica to explore an active volcano, Mount Erebus. The Dante project's robot science objectives were to demonstrate a real exploration mission, rough terrain locomotion, environmental survival, and self-sustained operation in the harsh Antarctic climate. The volcano science objective was to study the unique convecting magma lake inside Mount Erebus' inner crater. The expedition demonstrated the advancing state-of-art in mobile robotics and the future potential of robotic explorers. This paper details our objectives, describes the Dante robot, overviews what happened on the expedition and discusses what did and didn't work.     

Progress towards robotic exploration of extreme terrain

A high degree of mobility, reliability, and efficiency are needed for autonomous exploration of extreme terrain. These requirements have guided the development of the Ambler, a six-legged robot designed for planetary exploration. To address issues of efficiency and mobility, the Ambler is configured with a stacked arrangement of orthogonal legs and exhibits a unique circulating gait, where trailing legs recover directly from rear to front. The Ambler is designed to stably traverse a 30 degree slope while crossing meter sized features. The same three principles have provided many constraints on the design of a software system that autonomously navigates the Ambler through natural terrain using 3-D perception and a combined deliberative/reactive architecture. The software system has required research advances in real-time control, perception of rugged terrain, motion planning, task-level control, and system integration. This paper presents many of the factors that influenced the design of the Ambler and its software system. In particular, important assumptions regarding the mechanism, perception, planning, and control are presented and evaluated in light of experimental and theoretical research of this project.