Gravity is not a Pairwise Local Classical Channel

It is currently believed that there is no experimental evidence on possibly quantum features of gravity or gravity-motivated modifications of quantum mechanics. Here we show that single-atom interference experi- ments achieving large spatial superpositions can rule out a framework where the Newtonian gravitational inter- action is fundamentally classical in the information-theoretic sense: it cannot convey entanglement. Specifically, in this framework gravity acts pairwise between massive particles as classical channels, which effectively induce approximately Newtonian forces between the masses. The experiments indicate that if gravity does reduce to the pairwise Newtonian interaction between atoms at the low energies, this interaction cannot arise from the exchange of just classical information, and in principle has the capacity to create entanglement. We clarify that, contrary to current belief, the classical-channel description of gravity differs from the model of Diosi and Penrose, which is not constrained by the same data.Comment: 13 pages, 5 figures, 2 tables, Late

04251 -- Imaging Beyond the Pinhole Camera

From 13.06.04 to 18.06.04, the Dagstuhl Seminar 04251 ``Imaging Beyond the Pin-hole Camera. 12th Seminar on Theoretical Foundations of Computer Vision\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Relative Pose Uncertainty Quantification Using Lie Group Variational Filtering

The applications of visual sensing techniques have revolutionized the way autonomous systems perceive their environment on Earth. In space, the challenge of accurate perception has proven to be a difficult task. Due to adverse lighting conditions, high-noise images are common and degrade the performance of traditional feature-based estimation and perception algorithms. This work explores the applications of a variational filtering scheme founded in Lie Group theory to an autonomous rendezvous, proximity operations and docking problem. Two methodologies, a Monte Carlo approach and an Unscented Transform, for propagating uncertainty using a Lie Group Variational Filter are introduced and developed

An Overview of Kinematic and Calibration Models Using Internal/External Sensors or Constraints to Improve the Behavior of Spatial Parallel Mechanisms

This paper presents an overview of the literature on kinematic and calibration models of parallel mechanisms, the influence of sensors in the mechanism accuracy and parallel mechanisms used as sensors. The most relevant classifications to obtain and solve kinematic models and to identify geometric and non-geometric parameters in the calibration of parallel robots are discussed, examining the advantages and disadvantages of each method, presenting new trends and identifying unsolved problems. This overview tries to answer and show the solutions developed by the most up-to-date research to some of the most frequent questions that appear in the modelling of a parallel mechanism, such as how to measure, the number of sensors and necessary configurations, the type and influence of errors or the number of necessary parameters

Ono: an open platform for social robotics

In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform