Amanda Prorok

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Large numbers of collaborating robots are advantageous for solving distributed problems. In order to efficiently solve the task at hand, the robots often need accurate localization. In this work, we address the localization problem by developing a solution that has low computational and sensing requirements, and that is easily deployed on large robot teams(More)
Multi-robot systems can solve complex tasks that require the coordination of the team-member positions with respect to each other. While the development of ad-hoc relative positioning platforms embedding cheap off-the-shelf components is a practical choice, it leads not only to differences between the platforms themselves, but also to a high sensitivity to(More)
In the present study, we are interested in verifying how the progressive addition of constraints on communication and localization impact the performance of a swarm of small robots in shape formation tasks. Identified to be of importance in a swarm-user interaction context, the time required to construct a given spatial configuration is considered as a(More)
We propose a combined spatial and non-spatial probabilistic modeling methodology motivated by an inspection task performed by a group of miniature robots. Our models explicitly consider spatiality and yield accurate predictions on system performance. An agent’s spatial distribution over time is modeled by the Fokker–Planck diffusion model and complements(More)
Recent substantial progress in the domain of indoor positioning systems and a growing number of indoor locationbased applications are creating the need for systematic, efficient, and precise experimental methods able to assess the localization and perhaps also navigation performance of a given device. With hundreds of Khepera III robots in academic use(More)
Ultra-wideband (UWB) localization is one of the most promising indoor localization methods. Yet, non-line-ofsight (NLOS) positioning scenarios can potentially cause significant localization errors and remain a challenge. In this work, we propose a novel, probabilistic UWB TDOA error model which explicitly takes into account NLOS. In order to validate our(More)
This work is situated in the context of collaboratively solving the localization problem for unknown initial conditions. We address this problem with a novel, fully decentralized, real-time particle filter algorithm, designed to accommodate realistic robotic assumptions including noisy sensors, and asynchronous and lossy communication. In particular, we(More)
The efficiency of distributed sensor networks depends on an optimal trade-off between the usage of resources and data quality. The work in this paper addresses the problem of optimizing this trade-off in a self-configured distributed robotic sensor network, with respect to a user-defined objective function. We investigate a quadtree network topology and(More)
We are interested in a principled study of the impact of diversity in heterogeneous large-scale distributed robotic systems. In order to evaluate the implications of heterogeneity on performance, we consider the concrete problem of distributing a large group of robots among a set of tasks that require specialized capabilities in order to be completed. We(More)