Robust tracking of soccer robots using random finite sets

Maintaining a good estimation of the other robots' positions is crucial in soccer robotics. To tackle the data association problem, the proposed approach doesn't require explicit data association and integrates information shared by teammate robots.Advanced Mining Technology Center of the Universidad de Chile FONDECYT Project 116150

Robust RL-based map-less local planning: Using 2D point clouds as observations

In this letter, we propose a robust approach to train map-less navigation policies that rely on variable size 2D point clouds, using Deep Reinforcement Learning (Deep RL). The navigation policies are trained in simulations using the DDPG algorithm. Through experimental evaluations in simulated and real-world environments, we showcase the benefits of our approach when compared to more classical RL-based formulations: better performance, the possibility to interchange sensors at deployment time, and to easily augment the environment observability through sensor preprocessing and/or sensor fusion. Videos showing trajectories traversed by agents trained with the proposed approach can be found in https://youtu.be/AzvRJyN6rwQ.Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) CONICYT FONDECYT 1201170 ANID-PIA AFB180004 CONICYTPFCHA/Magister Nacional/2018 2218213

A bayesian based methodology for indirect object search

The main goal of this paper is to propose a Bayesian based methodology for implementing robot informed search for objects. The methodology uses convolutions between observation likelihoods of secondary objects and spatial relation masks for estimating the probability map of the object being searched for, and also a search procedure that uses this probability map. A method for computing complex spatial relation masks by using a basis composed of basic relation masks and a database of co-occurrences of objects is used. Each basic relation mask corresponds to a qualitative spatial relation (QSR), such as: 'very near', 'near', or 'far'. The search procedure takes into account the probability that the main object can be in different regions on the map and the distance to those regions. Also, the object search procedure is able to detect objects and generate new plans while moving. The proposed methodology is compared with uninformed and alternative informed search approaches using simulations and real-world experiments with a service robot. In simulations, the use of the proposed methodology increases the detection rate from 28% (direct uninformed search) to 79%, when the main object can be detected within a maximum distance of 1 meter. In the real world experiments, the use of the proposed methodology increases the detection rate from 40% (direct uninformed search) to 87% when using convolutions with soft masks, global search, and information on the positive detection of secondary objects. The detection rates obtained when using the proposed methodology are also much higher than those obtained by alternative informed search methods, both in the simulated and in the real-world experiments.Fondecyt 1130153 116150

Decentralized reinforcement learning of robot behaviors

A multi-agent methodology is proposed for Decentralized Reinforcement Learning (DRL) of individual behaviors in problems where multi-dimensional action spaces are involved. When using this methodology, sub-tasks are learned in parallel by individual agents working toward a common goal. In addition to proposing this methodology, three specific multi agent DRL approaches are considered: DRL-Independent, DRL Cooperative Adaptive (CA), and DRL-Lenient. These approaches are validated and analyzed with an extensive empirical study using four different problems: 3D Mountain Car, SCARA Real-Time Trajectory Generation, Ball-Dribbling in humanoid soccer robotics, and Ball Pushing using differential drive robots. The experimental validation provides evidence that DRL implementations show better performances and faster learning times than their centralized counterparts, while using less computational resources. DRL-Lenient and DRL-CA algorithms achieve the best final performances for the four tested problems, outperforming their DRL-Independent counterparts. Furthermore, the benefits of the DRLLenient and DRL-CA are more noticeable when the problem complexity increases and the centralized scheme becomes intractable given the available computational resources and training time.CONICYT CONICYT-PCHA/Doctorado Nacional/2013-63130183 FONDECYT 1161500 European Regional Development Fund under the project Robotics 4 Industry 4.0 CZ.02.1.01/0.0/0.0/15_003/000047

Interactive learning of temporal features for control. Shaping Policies and state representations from human feedback

Current ongoing industry revolution demands more flexible products, including robots in household environments and medium-scale factories. Such robots should be able to adapt to new conditions and environments and be programmed with ease. As an example, let us suppose that there are robot manipulators working on an industrial production line and that they need to perform a new task. If these robots were hard coded, it could take days to adapt them to the new settings, which would stop production at the factory. Robots that non-expert humans could easily program would speed up the process considerably.Netherlands Organization for Scientific Research project Cognitive Robots for Flexible Agro-Food Technology P17-01 European Research Council (ERC) 804907 Chile's National Fund for Scientific and Technological Development project (FONDECYT) 1201170 Chile's Associative Research Program of the National Research and Development Agency (ANID/PIA) AFB18000

Robotics research in Chile: addressing the needs of the local mining industry at the Advanced Mining Technology Center

The development of research in robotics in a developing country is a challenging task. Factors such as low research funds, low trust from local companies and the government, and a small number of qualified researchers hinder the development of strong, local research groups. In this article, and as a case of study, we present our research group in robotics at the Advanced Mining Technology Center of the Universidad de Chile, and the way in which we have addressed these challenges. In 2008, we decided to focus our research efforts in mining, which is the main industry in Chile. We observed that this industry has needs in terms of safety, productivity, operational continuity, and environmental care. All these needs could be addressed with robotics and automation technology. In a first stage, we concentrate ourselves in building capabilities in field robotics, starting with the automation of a commercial vehicle. An important outcome of this project was the earn of the local mining industry confidence. Then, in a second stage started in 2012, we began working with the local mining industry in technological projects. In this article, we describe three of the technological projects that we have developed with industry support: (i) an autonomous vehicle for mining environments without global positioning system coverage; (ii) the inspection of the irrigation flow in heap leach piles using unmanned aerial vehicles and thermal cameras; and (iii) an enhanced vision system for vehicle teleoperation in adverse climatic conditionsFONDECYT (CHILE) Grant 1161500 GIZ (Germany) Grant "Accesible automation for a more efficient and safer underground mining in Chile'

TVI- Arquitectura y Construcción - AR313 - 202102

Descripción: El curso TVI-Arquitectura y construcción introduce al estudiante en el conocimiento de las necesidades constructivas del proyecto arquitectónico y en la aplicación de los sistema estructurales; en la coordinación de sistemas estructurales para hacer posible que los sótanos de estacionamiento calcen sobre plantas de desarrollo habitacional, que los ductos de instalaciones eléctricas y sanitarias tengan continuidad, etc. Se diseñan pequeños edificios de oficinas, fábricas, centros comerciales, clínicas, complejos deportivos, etc. Propósito: Desarrollar propuestas arquitectónicas cuya concepción involucre la necesidad de pensar en sistemas estructurales adecuados, un correcto dimensionamiento para las necesidades materiales del proyecto (tales como estacionamiento, traslado de muebles, y seguridad) La construcción implica decidir una lógica estructural, por el comportamiento del material, y la expresión arquitectónica en coherencia con el tema ¿organización y funcionamiento- y el lugar. La asignatura contribuye al desarrollo de las competencias específicas de la carrera: Diseño Fundamentado, que corresponde a los criterios NAAB PC2, PC3, PC8, PC5, SC3, SC5, así como, Técnica y Construcción que corresponde a los criterios NAAB SC1, SC4, SC6; ambas en el nivel de logro 2. Tiene como requisito la asignatura de AR309 TV - Arquitectura y Medio Ambient

TVI - Arquitectura y Construcción - AR323 - 202101

Descripción: El curso TVI-Arquitectura y construcción introduce al estudiante en el conocimiento de las necesidades constructivas del proyecto arquitectónico y en la aplicación de los sistema estructurales; en la coordinación de sistemas estructurales para hacer posible que los sótanos de estacionamiento calcen sobre plantas de desarrollo habitacional, que los ductos de instalaciones eléctricas y sanitarias tengan continuidad, etc. Se diseñan pequeños edificios de oficinas, fábricas, centros comerciales, clínicas, complejos deportivos, etc. Propósito: Desarrollar propuestas arquitectónicas cuya concepción involucre la necesidad de pensar en sistemas estructurales adecuados, un correcto dimensionamiento para las necesidades materiales del proyecto (tales como estacionamiento, traslado de muebles, y seguridad) La construcción implica decidir una lógica estructural, por el comportamiento del material, y la expresión arquitectónica en coherencia con el tema ¿organización y funcionamiento- y el lugar. La asignatura contribuye al desarrollo de las competencias específicas de la carrera: Diseño Fundamentado, que corresponde a los criterios NAAB PC2, PC3, PC8, PC5, SC3, SC5, así como, Técnica y Construcción que corresponde a los criterios NAAB SC1, SC4, SC6; ambas en el nivel de logro 2. Tiene como requisito la asignatura de AR309 TV - Arquitectura y Medio Ambient