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We present OPTIMo: an Online Probabilistic Trust Inference Model for quantifying the degree of trust that a human supervisor has in an autonomous robot "worker". Represented as a Dynamic Bayesian Network, OPTIMo infers beliefs over the human's moment-to-moment latent trust states, based on the history of observed interaction experiences. A separate model(More)
We describe the design and implementation of a fiducial marker system that encodes data in the frequency spectrum of a synthetic image. This distinctive approach to marker synthesis and data encoding allows for partial data extraction in adverse imaging conditions, and can significantly extend the detection range through graceful data degradation.(More)
In this paper we describe a heterogeneous multi-robot system for assisting scientists in environmental monitoring tasks, such as the inspection of marine ecosystems. This team of robots is comprised of a fixed-wing aerial vehicle, an autonomous airboat, and an agile legged underwater robot. These robots interact with off-site scientists and operate in a(More)
We describe a framework that combines a software development paradigm, a software visualization technique, and a tool for robot programming. This infrastructure is called “Graphical State Space Programming” (GSSP), and allows robot application programs to be decomposed and visualized within state-dependent views. Our approach simplifies and(More)
We present the adaptation of an optimal terrain coverage algorithm for the aerial robotics domain. The general strategy involves computing a trajectory through a known environment with obstacles that ensures complete coverage of the terrain while minimizing path repetition. We introduce a system that applies and extends this generic algorithm to achieve(More)
We describe an interaction paradigm for controlling a robot using hand gestures. In particular, we are interested in the control of an underwater robot by an on-site human operator. Under this context, vision-based control is very attractive, and we propose a robot control and programming mechanism based on visual symbols. A human operator presents(More)
We present an integration of classical computer vision techniques to achieve real-time autonomous steering of an unmanned aircraft along the boundary of different regions. Using an unified conceptual framework, we illustrate solutions for tracking coastlines and for following roads surrounded by forests. In particular, we exploit color and texture(More)
A gesture-based interaction framework is presented for controlling mobile robots. This natural interaction paradigm has few physical requirements, and thus can be deployed in many restrictive and challenging environments. We present an implementation of this scheme in the control of an underwater robot by an on-site human operator. The operator performs(More)
We describe a model of “trust” in human-robot systems that is inferred from their interactions, and inspired by similar concepts relating to trust among humans. This computable quantity allows a robot to estimate the extent to which its performance is consistent with a human's expectations, with respect to task demands. Our trust model drives(More)