TAX-Pose: Task-Specific Cross-Pose Estimation for Robot Manipulation

How do we imbue robots with the ability to efficiently manipulate unseen objects and transfer relevant skills based on demonstrations? End-to-end learning methods often fail to generalize to novel objects or unseen configurations. Instead, we focus on the task-specific pose relationship between relevant parts of interacting objects. We conjecture that this relationship is a generalizable notion of a manipulation task that can transfer to new objects in the same category; examples include the relationship between the pose of a pan relative to an oven or the pose of a mug relative to a mug rack. We call this task-specific pose relationship "cross-pose" and provide a mathematical definition of this concept. We propose a vision-based system that learns to estimate the cross-pose between two objects for a given manipulation task using learned cross-object correspondences. The estimated cross-pose is then used to guide a downstream motion planner to manipulate the objects into the desired pose relationship (placing a pan into the oven or the mug onto the mug rack). We demonstrate our method's capability to generalize to unseen objects, in some cases after training on only 10 demonstrations in the real world. Results show that our system achieves state-of-the-art performance in both simulated and real-world experiments across a number of tasks. Supplementary information and videos can be found at https://sites.google.com/view/tax-pose/home.Comment: Conference on Robot Learning (CoRL), 2022. Supplementary material is available at https://sites.google.com/view/tax-pose/hom

Uniformity in the Wiener-Wintner theorem for nilsequences

We prove a uniform extension of the Wiener-Wintner theorem for nilsequences due to Host and Kra and a nilsequence extension of the topological Wiener-Wintner theorem due to Assani. Our argument is based on (vertical) Fourier analysis and a Sobolev embedding theorem.Comment: v3: 18 p., proof that the cube construction produces compact homogeneous spaces added, measurability issues in the proof of Theorem 1.5 addressed. We thank the anonymous referees for pointing out these gaps in v

Astrometry with the Keck-Interferometer: the ASTRA project and its science

The sensitivity and astrometry upgrade ASTRA of the Keck Interferometer is introduced. After a brief overview of the underlying interferometric principles, the technology and concepts of the upgrade are presented. The interferometric dual-field technology of ASTRA will provide the KI with the means to observe two objects simultaneously, and measure the distance between them with a precision eventually better than 100 uas. This astrometric functionality of ASTRA will add a unique observing tool to fields of astrophysical research as diverse as exo-planetary kinematics, binary astrometry, and the investigation of stars accelerated by the massive black hole in the center of the Milky Way as discussed in this contribution.Comment: 22 pages, 10 figures (low resolution), contribution to the summerschool "Astrometry and Imaging with the Very Large Telescope Interferometer", 2 - 13 June, 2008, Keszthely, Hungary, corrected authorlis

The environmental costs and benefits of high-yield farming

How we manage farming and food systems to meet rising demand is pivotal to the future of biodiversity. Extensive field data suggest impacts on wild populations would be greatly reduced through boosting yields on existing farmland so as to spare remaining natural habitats. High-yield farming raises other concerns because expressed per unit area it can generate high levels of externalities such as greenhouse gas (GHG) emissions and nutrient losses. However, such metrics underestimate the overall impacts of lower-yield systems, so here we develop a framework that instead compares externality and land costs per unit production. Applying this to diverse datasets describing the externalities of four major farm sectors reveals that, rather than involving trade-offs, the externality and land costs of alternative production systems can co-vary positively: per unit production, land-efficient systems often produce lower externalities. For GHG emissions these associations become more strongly positive once forgone sequestration is included. Our conclusions are limited: remarkably few studies report externalities alongside yields; many important externalities and farming systems are inadequately measured; and realising the environmental benefits of high-yield systems typically requires additional measures to limit farmland expansion. Yet our results nevertheless suggest that trade-offs among key cost metrics are not as ubiquitous as sometimes perceived. There is an author correction to this article. See: https://doi.org/10.1038/s41893-018-0138-5We are grateful for funding from the Cambridge Conservation Initiative Collaborative Fund and Arcadia, the Grantham Foundation for the Protection of the Environment, the Kenneth Miller Trust the UK-China Virtual Joint Centre for Agricultural Nitrogen (CINAg, 780 BB/N013468/1, financed by the Newton Fund via BBSRC and NERC), BBSRC (BBS/E/C/000I0330), DEVIL (NE/M021327/1), U-GRASS (NE/M016900/1), Soils-R-GRREAT (NE/P019455/1), N-Circle (BB/N013484/1), BBSRC Soil to Nutrition (S2N) strategic programme (BBS/E/C/000I0330), UNAM-PAPIIT (IV200715), the Belmont Forum/FACEE-JPI (NE/M021327/1 ‘DEVIL’), and the Cambridge Earth System Science NERC DTP (NE/L002507/1); AB is supported by a Royal Society Wolfson Research Merit award