Active End-Effector Pose Selection for Tactile Object Recognition through Monte Carlo Tree Search

This paper considers the problem of active object recognition using touch only. The focus is on adaptively selecting a sequence of wrist poses that achieves accurate recognition by enclosure grasps. It seeks to minimize the number of touches and maximize recognition confidence. The actions are formulated as wrist poses relative to each other, making the algorithm independent of absolute workspace coordinates. The optimal sequence is approximated by Monte Carlo tree search. We demonstrate results in a physics engine and on a real robot. In the physics engine, most object instances were recognized in at most 16 grasps. On a real robot, our method recognized objects in 2--9 grasps and outperformed a greedy baseline.Comment: Accepted to International Conference on Intelligent Robots and Systems (IROS) 201

Active End-Effector Pose Selection for Tactile Object Recognition through Monte Carlo Tree Search

This paper considers the problem of active object recognition using touch only. The focus is on adaptively selecting a sequence of wrist poses that achieves accurate recognition by enclosure grasps. It seeks to minimize the number of touches and maximize recognition confidence. The actions are formulated as wrist poses relative to each other, making the algorithm independent of absolute workspace coordinates. The optimal sequence is approximated by Monte Carlo tree search. We demonstrate results in a physics engine and on a real robot. In the physics engine, most object instances were recognized in at most 16 grasps. On a real robot, our method recognized objects in 2--9 grasps and outperformed a greedy baseline.Comment: Accepted to International Conference on Intelligent Robots and Systems (IROS) 201

Tactile Perception And Visuotactile Integration For Robotic Exploration

As the close perceptual sibling of vision, the sense of touch has historically received less than deserved attention in both human psychology and robotics. In robotics, this may be attributed to at least two reasons. First, it suffers from the vicious cycle of immature sensor technology, which causes industry demand to be low, and then there is even less incentive to make existing sensors in research labs easy to manufacture and marketable. Second, the situation stems from a fear of making contact with the environment, avoided in every way so that visually perceived states do not change before a carefully estimated and ballistically executed physical interaction. Fortunately, the latter viewpoint is starting to change. Work in interactive perception and contact-rich manipulation are on the rise. Good reasons are steering the manipulation and locomotion communities’ attention towards deliberate physical interaction with the environment prior to, during, and after a task. We approach the problem of perception prior to manipulation, using the sense of touch, for the purpose of understanding the surroundings of an autonomous robot. The overwhelming majority of work in perception for manipulation is based on vision. While vision is a fast and global modality, it is insufficient as the sole modality, especially in environments where the ambient light or the objects therein do not lend themselves to vision, such as in darkness, smoky or dusty rooms in search and rescue, underwater, transparent and reflective objects, and retrieving items inside a bag. Even in normal lighting conditions, during a manipulation task, the target object and fingers are usually occluded from view by the gripper. Moreover, vision-based grasp planners, typically trained in simulation, often make errors that cannot be foreseen until contact. As a step towards addressing these problems, we present first a global shape-based feature descriptor for object recognition using non-prehensile tactile probing alone. Then, we investigate in making the tactile modality, local and slow by nature, more efficient for the task by predicting the most cost-effective moves using active exploration. To combine the local and physical advantages of touch and the fast and global advantages of vision, we propose and evaluate a learning-based method for visuotactile integration for grasping

Physics-Based Modelling and Simulation of Multibeam Echosounder Perception for Autonomous Underwater Manipulation

17 USC 105 interim-entered record; under review.The article of record as published may be found at https://doi.org/10.3389/frobt.2021.706646One of the key distinguishing aspects of underwater manipulation tasks is the perception challenges of the ocean environment, including turbidity, backscatter, and lighting effects. Consequently, underwater perception often relies on sonar-based measurements to estimate the vehicle’s state and surroundings, either standalone or in concert with other sensing modalities, to support the perception necessary to plan and control manipulation tasks. Simulation of the multibeam echosounder, while not a substitute for in-water testing, is a critical capability for developing manipulation strategies in the complex and variable ocean environment. Although several approaches exist in the literature to simulate synthetic sonar images, the methods in the robotics community typically use image processing and video rendering software to comply with real-time execution requirements. In addition to a lack of physics-based interaction model between sound and the scene of interest, several basic properties are absent in these rendered sonar images–notably the coherent imaging system and coherent speckle that cause distortion of the object geometry in the sonar image. To address this deficiency, we present a physics-based multibeam echosounder simulation method to capture these fundamental aspects of sonar perception. A point-based scattering model is implemented to calculate the acoustic interaction between the target and the environment. This is a simplified representation of target scattering but can produce realistic coherent image speckle and the correct point spread function. The results demonstrate that this multibeam echosounder simulator generates qualitatively realistic images with high efficiency to provide the sonar image and the physical time series signal data. This synthetic sonar data is a key enabler for developing, testing, and evaluating autonomous underwater manipulation strategies that use sonar as a component of perception.This research was performed while the author held an NRC Research Associateship award at Field Robotics Laboratory, Naval Postgraduate Schoo

Maintenance Optimization and Inspection Planning of Wind Energy Assets: Models, Methods and Strategies

Designing cost-effective inspection and maintenance programmes for wind energy farms is a complex task involving a high degree of uncertainty due to diversity of assets and their corresponding damage mechanisms and failure modes, weather-dependent transport conditions, unpredictable spare parts demand, insufficient space or poor accessibility for maintenance and repair, limited availability of resources in terms of equipment and skilled manpower, etc. In recent years, maintenance optimization has attracted the attention of many researchers and practitioners from various sectors of the wind energy industry, including manufacturers, component suppliers, maintenance contractors and others. In this paper, we propose a conceptual classification framework for the available literature on maintenance policy optimization and inspection planning of wind energy systems and structures (turbines, foundations, power cables and electrical substations). The developed framework addresses a wide range of theoretical and practical issues, including the models, methods, and the strategies employed to optimise maintenance decisions and inspection procedures in wind farms. The literature published to date on the subject of this article is critically reviewed and several research gaps are identified. Moreover, the available studies are systematically classified using different criteria and some research directions of potential interest to operational researchers are highlighted

Potential for a Circular Autopoietic Economy on Canavese Territory

The aim of this gigamap is to describe and summarize a student work carried out during the semester course Open Systems Design at Politecnico Torino. The map is one of the outputs from an analysis of the Canavese, Piedmont region and subsequently an in-depth study of the relationships and “flows” with certain “currencies” between some selected economic and public actors. Canavese is a historical-geographical area located in the province of Turin, Italy; it’s full of great natural and geological spots, with a strong enogastronomic identity, historical re-enactments, a well-known manufacture sector like the ceramic of Castellamonte, as well as the leading high-tech branch like Arduino. Through the approach deriving from systemic design, it was possible to identify some strategies for the creation of new networks aimed at transforming the economy and production processes from linear to circular approach. Five types of “circular flows” were assessed and “designed into” the current linear system, thus proposing an improved economy based on circularity: flows of matter (energy/CO2, water, materials), economic flows, and social flows. The Gigamap will be presented to stakeholders in a public hearing and supposedly be used to illustrate and incubate a circular economy that is more resilient and more regenerative. Reading the map The reading should start at the top left, where the abstract is located, next, there is an outline that shows the connections between the five topics investigated. Subsequently, there is a timeline with some fundamental events in the history of the Canavese. In the center there is the circularity map with the main cities, focusing on new opportunities of circular flows between the 15 analysed economic actors. At the bottom, some general data and on the right a brief description of the role and territorial qualities of the companies. Lastly, there is a summary of the emerging properties

Children’s and adolescents’ rising animal-source food intakes in 1990–2018 were impacted by age, region, parental education and urbanicity

Animal-source foods (ASF) provide nutrition for children and adolescents’ physical and cognitive development. Here, we use data from the Global Dietary Database and Bayesian hierarchical models to quantify global, regional and national ASF intakes between 1990 and 2018 by age group across 185 countries, representing 93% of the world’s child population. Mean ASF intake was 1.9 servings per day, representing 16% of children consuming at least three daily servings. Intake was similar between boys and girls, but higher among urban children with educated parents. Consumption varied by age from 0.6 at <1 year to 2.5 servings per day at 15–19 years. Between 1990 and 2018, mean ASF intake increased by 0.5 servings per week, with increases in all regions except sub-Saharan Africa. In 2018, total ASF consumption was highest in Russia, Brazil, Mexico and Turkey, and lowest in Uganda, India, Kenya and Bangladesh. These findings can inform policy to address malnutrition through targeted ASF consumption programmes.publishedVersio

Incident type 2 diabetes attributable to suboptimal diet in 184 countries

The global burden of diet-attributable type 2 diabetes (T2D) is not well established. This risk assessment model estimated T2D incidence among adults attributable to direct and body weight-mediated effects of 11 dietary factors in 184 countries in 1990 and 2018. In 2018, suboptimal intake of these dietary factors was estimated to be attributable to 14.1 million (95% uncertainty interval (UI), 13.8–14.4 million) incident T2D cases, representing 70.3% (68.8–71.8%) of new cases globally. Largest T2D burdens were attributable to insufficient whole-grain intake (26.1% (25.0–27.1%)), excess refined rice and wheat intake (24.6% (22.3–27.2%)) and excess processed meat intake (20.3% (18.3–23.5%)). Across regions, highest proportional burdens were in central and eastern Europe and central Asia (85.6% (83.4–87.7%)) and Latin America and the Caribbean (81.8% (80.1–83.4%)); and lowest proportional burdens were in South Asia (55.4% (52.1–60.7%)). Proportions of diet-attributable T2D were generally larger in men than in women and were inversely correlated with age. Diet-attributable T2D was generally larger among urban versus rural residents and higher versus lower educated individuals, except in high-income countries, central and eastern Europe and central Asia, where burdens were larger in rural residents and in lower educated individuals. Compared with 1990, global diet-attributable T2D increased by 2.6 absolute percentage points (8.6 million more cases) in 2018, with variation in these trends by world region and dietary factor. These findings inform nutritional priorities and clinical and public health planning to improve dietary quality and reduce T2D globally.publishedVersio