Perception-driven sparse graphs for optimal motion planning

Most existing motion planning algorithms assume that a map (of some quality) is fully determined prior to generating a motion plan. In many emerging applications of robotics, e.g., fast-moving agile aerial robots with constrained embedded computational platforms and visual sensors, dense maps of the world are not immediately available, and they are computationally expensive to construct. We propose a new algorithm for generating plan graphs which couples the perception and motion planning processes for computational efficiency. In a nutshell, the proposed algorithm iteratively switches between the planning sub-problem and the mapping sub-problem, each updating based on the other until a valid trajectory is found. The resulting trajectory retains a provable property of providing an optimal trajectory with respect to the full (unmapped) environment, while utilizing only a fraction of the sensing data in computational experiments.Comment: 2018 IEEE/RSJ International Conference on Intelligent Robots and System

Perception-driven optimal motion planning under resource constraints

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Applied Ocean Science & Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2019.Over the past few years there has been a new wave of interest in fully autonomous robots operating in the real world, with applications from autonomous driving to search and rescue. These robots are expected to operate at high speeds in unknown, unstructured environments using only onboard sensing and computation, presenting significant challenges for high performance autonomous navigation. To enable research in these challenging scenarios, the first part of this thesis focuses on the development of a custom high-performance research UAV capable of high speed autonomous flight using only vision and inertial sensors. This research platform was used to develop stateof-the-art onboard visual inertial state estimation at high speeds in challenging scenarios such as flying through window gaps. While this platform is capable of high performance state estimation and control, its capabilities in unknown environments are severely limited by the computational costs of running traditional vision-based mapping and motion planning algorithms on an embedded platform. Motivated by these challenges, the second part of this thesis presents an algorithmic approach to the problem of motion planning in an unknown environment when the computational costs of mapping all available sensor data is prohibitively high. The algorithm is built around a tree of dynamically feasible and free space optimal trajectories to the goal state in configuration space. As the algorithm progresses it iteratively switches between processing new sensor data and locally updating the search tree. We show that the algorithm produces globally optimal motion plans, matching the optimal solution for the case with the full (unprocessed) sensor data, while only processing a subset of the data. The mapping and motion planning algorithm is demonstrated on a number of test systems, with a particular focus on a six-dimensional thrust limited model of a quadrotor

Multi-modal survey of Adélie penguin mega-colonies reveals the Danger Islands as a seabird hotspot

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 8 (2018): 3926, doi:10.1038/s41598-018-22313-w.Despite concerted international effort to track and interpret shifts in the abundance and distribution of Adélie penguins, large populations continue to be identified. Here we report on a major hotspot of Adélie penguin abundance identified in the Danger Islands off the northern tip of the Antarctic Peninsula (AP). We present the first complete census of Pygoscelis spp. penguins in the Danger Islands, estimated from a multi-modal survey consisting of direct ground counts and computer-automated counts of unmanned aerial vehicle (UAV) imagery. Our survey reveals that the Danger Islands host 751,527 pairs of Adélie penguins, more than the rest of AP region combined, and include the third and fourth largest Adélie penguin colonies in the world. Our results validate the use of Landsat medium-resolution satellite imagery for the detection of new or unknown penguin colonies and highlight the utility of combining satellite imagery with ground and UAV surveys. The Danger Islands appear to have avoided recent declines documented on the Western AP and, because they are large and likely to remain an important hotspot for avian abundance under projected climate change, deserve special consideration in the negotiation and design of Marine Protected Areas in the region.We gratefully acknowledge the financial support of the Dalio Foundation, Inc. through the Dalio Explore Fund, which provided all the financing for the Danger Island Expedition. We would like to thank additional support for analysis from the National Science Foundation (NSF PLR&GSS 1255058 - H.J.L. and P.M.; NSF PLR 1443585 – M.J.P.) and the National Aeronautical and Space Administration (NNX14AC32G; H.J.L. and M.S.). Geospatial support for the analysis of high resolution satellite imagery provided by the Polar Geospatial Center under NSF PLR awards 1043681 & 1559691

Revisiting Folk Moral Realism

Moral realists believe that there are objective moral truths. According to one of the most prominent arguments in favour of this view, ordinary people experience morality as realist-seeming, and we have therefore prima facie reason to believe that realism is true. Some proponents of this argument have claimed that the hypothesis that ordinary people experience morality as realist-seeming is supported by psychological research on folk metaethics. While most recent research has been thought to contradict this claim, four prominent earlier studies (by Goodwin and Darley, Wainryb et al., Nichols, and Nichols and Folds-Bennett) indeed seem to suggest a tendency towards realism. My aim in this paper is to provide a detailed internal critique of these four studies. I argue that, once interpreted properly, all of them turn out in line with recent research. They suggest that most ordinary people experience morality as “pluralist-” rather than realist-seeming, i.e., that ordinary people have the intuition that realism is true with regard to some moral issues, but variants of anti-realism are true with regard to others. This result means that moral realism may be less well justified than commonly assumed

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

Perception-driven optimal motion planning under resource constraints

Thesis (Ph. D.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 105-112).Over the past few years there has been a new wave of interest in fully autonomous robots operating in the real world, with applications from autonomous driving to search and rescue. These robots are expected to operate at high speeds in unknown, unstructured environments using only onboard sensing and computation, presenting significant challenges for high performance autonomous navigation. To enable research in these challenging scenarios, the first part of this thesis focuses on the development of a custom high-performance research UAV capable of high speed autonomous flight using only vision and inertial sensors. This research platform was used to develop stateof- the-art onboard visual inertial state estimation at high speeds in challenging scenarios such as flying through window gaps. While this platform is capable of high performance state estimation and control, its capabilities in unknown environments are severely limited by the computational costs of running traditional vision-based mapping and motion planning algorithms on an embedded platform. Motivated by these challenges, the second part of this thesis presents an algorithmic approach to the problem of motion planning in an unknown environment when the computational costs of mapping all available sensor data is prohibitively high. The algorithm is built around a tree of dynamically feasible and free space optimal trajectories to the goal state in configuration space. As the algorithm progresses it iteratively switches between processing new sensor data and locally updating the search tree. We show that the algorithm produces globally optimal motion plans, matching the optimal solution for the case with the full (unprocessed) sensor data, while only processing a subset of the data. The mapping and motion planning algorithm is demonstrated on a number of test systems, with a particular focus on a six-dimensional thrust limited model of a quadrotor.Supported in part by NVIDIA, MIT Lincoln Laboratory, MIT-WHOI Joint Program, and JD.comby Thomas Sayre-McCord.Thesis (Ph. D.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 201

Swimming speeds of polychaete larvae collected near deep-sea hydrothermal vents

For benthic fauna endemic to hydrothermal vents, larval dispersal in the plankton is required for maintenance of populations and colonization of new vents. Dispersal distances in the plankton are expected to be influenced by vertical positioning into horizontal currents, and larval survival in the plankton as well as encounter rates for settlement cues may be influenced by swimming speed. Here, we present the first quantitative measurements of swimming speeds of polychaete larvae collected near deep-sea hydrothermal vents. We focused on three polychaete larvae of different morphotypes, with two morphotypes identified genetically to Capitellidae and Spionidae. Mean swimming speeds and helical parameters of the deep-sea polychaete larvae (measured at 1 atm) were similar to values reported for shallow-water polychaete larvae, with mean helical 3D swimming speeds ranging from 0.8-1.4 mm.s(-1). To account for swimming that deviated from helical patterns, we developed a new method to reconstruct 3D swimming trajectories, using the 2D track and larval orientation. Speeds were generally faster for downward swimming, with mean vertical displacement speeds ranging from 0.6-0.8 mm.s(-1) downward as compared with 0.2-0.6 mm.s(-1) upward. Mean swimming speeds and helical parameters differed among the individuals. Our results are a first step towards constraining a behavioral component in models of larval dispersal between deep-sea hydrothermal vents