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Model-based synthesis of distributed controllers for multi-robot systems is commonly approached in either a top-down or bottom-up fashion. In this paper, we investigate the experimental challenges of both approaches, with a special emphasis on resource-con ...
We compare six different algorithms for localizing odor sources with mobile robots. Three algorithms are bio-inspired and mimic the behavior of insects when exposed to airborne pheromones. Two algorithms are based on probability and information theory, and ...
The present work tackles integration in mobile robotics. Integration is often considered to be a mere technique, unworthy of scientific investigation. On the contrary, we show that integrating capabilities in a mobile robot entails new questions that the p ...
This paper introduces a novel batch optimization based calibration framework for legged robots. Given a nondegenerate calibration dataset and considering the stochastic models of the sensors, the task is formulated as a maximum likelihood problem. In order ...
Legged robots come in a range of sizes and capabilities. By combining these robots into heterogeneous teams, joint locomotion and perception tasks can be achieved by utilizing the diversified features of each robot. In this work we present a framework for ...
The framework of graphical models is a cornerstone of applied Statistics, allowing for an intuitive graphical specification of the main features of a model, and providing a basis for general Bayesian inference computations though belief propagation (BP). I ...
We propose a semiparametric model for regression problems involving multiple response variables. Conditional dependencies between the responses are represented through a linear mixture of Gaussian processes. We propose an efficient approximate inference sc ...
Robots capable of hover flight in constrained indoor environments have many applications, however their range is constrained by the high energetic cost of airborne locomotion. Perching allows flying robots to scan their environment without the need to rema ...
Despite tremendous advances in robotics, we are still amazed by the proficiency with which humans perform movements. Even new waves of robotic systems still rely heavily on hardcoded motions with a limited ability to react autonomously and robustly to a dy ...
We propose a semiparametric model for regression and classification problems involving multiple response variables. The model makes use of a set of Gaussian processes to model the relationship to the inputs in a nonparametric fashion. Conditional dependenc ...
