Software tools for the cognitive development of autonomous robots

Robotic systems are evolving towards higher degrees of autonomy. This paper reviews the cognitive tools available nowadays for the fulfilment of abstract or long-term goals as well as for learning and modifying their behaviour.Peer ReviewedPostprint (author's final draft

Survey on assembly sequencing: a combinatorial and geometrical perspective

A systematic overview on the subject of assembly sequencing is presented. Sequencing lies at the core of assembly planning, and variants include finding a feasible sequence—respecting the precedence constraints between the assembly operations—, or determining an optimal one according to one or several operational criteria. The different ways of representing the space of feasible assembly sequences are described, as well as the search and optimization algorithms that can be used. Geometry plays a fundamental role in devising the precedence constraints between assembly operations, and this is the subject of the second part of the survey, which treats also motion in contact in the context of the actual performance of assembly operations.Peer ReviewedPostprint (author’s final draft

Survey on model-based manipulation planning of deformable objects

A systematic overview on the subject of model-based manipulation planning of deformable objects is presented. Existing modelling techniques of volumetric, planar and linear deformable objects are described, emphasizing the different types of deformation. Planning strategies are categorized according to the type of manipulation goal: path planning, folding/unfolding, topology modifications and assembly. Most current contributions fit naturally into these categories, and thus the presented algorithms constitute an adequate basis for future developments.Preprin

Visual grasp point localization, classification and state recognition in robotic manipulation of cloth: an overview

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Cloth manipulation by robots is gaining popularity among researchers because of its relevance, mainly (but not only) in domestic and assistive robotics. The required science and technologies begin to be ripe for the challenges posed by the manipulation of soft materials, and many contributions have appeared in the last years. This survey provides a systematic review of existing techniques for the basic perceptual tasks of grasp point localization, state estimation and classification of cloth items, from the perspective of their manipulation by robots. This choice is grounded on the fact that any manipulative action requires to instruct the robot where to grasp, and most garment handling activities depend on the correct recognition of the type to which the particular cloth item belongs and its state. The high inter- and intraclass variability of garments, the continuous nature of the possible deformations of cloth and the evident difficulties in predicting their localization and extension on the garment piece are challenges that have encouraged the researchers to provide a plethora of methods to confront such problems, with some promising results. The present review constitutes for the first time an effort in furnishing a structured framework of these works, with the aim of helping future contributors to gain both insight and perspective on the subjectPeer ReviewedPostprint (author's final draft

Robot learning from demonstration of force-based tasks with multiple solution trajectories

A learning framework with a bidirectional communication channel is proposed, where a human performs several demonstrations of a task using a haptic device (providing him/her with force-torque feedback) while a robot captures these executions using only its force-based perceptive system. Our work departs from the usual approaches to learning by demonstration in that the robot has to execute the task blindly, relying only on force-torque perceptions, and, more essential, we address goal-driven manipulation tasks with multiple solution trajectories, whereas most works tackle tasks that can be learned by just finding a generalization at the trajectory level. To cope with these multiple-solution tasks, in our framework demonstrations are represented by means of a Hidden Markov Model (HMM) and the robot reproduction of the task is performed using a modified version of Gaussian Mixture Regression that incorporates temporal information (GMRa) through the forward variable of the HMM. Also, we exploit the haptic device as a teaching and communication tool in a human-robot interaction context, as an alternative to kinesthetic-based teaching systems. Results show that the robot is able to learn a container-emptying task relying only on force-based perceptions and to achieve the goal from several non-trained initial conditions.Postprint (author’s final draft

ヒトの身体防御システムで働く環境毒によるCa2+シグナリング機構の研究

早大学位記番号:新7552早稲田大

DEM simulation of triaxial tests of railway ballast fouled with desert sand

Some high-speed rail lines go through desert zones where sand particles transported by winds may foul track ballast layers. This fouling can be troublesome since it increases the stiffness of the layer and reduces its capacity to absorb vibrations from the rolling stock. We are studying this phenomenon through both laboratory and numerical experiments. In the laboratory, we performed two kinds of experiments: 9 inches triaxial tests and physical modelling in the CEDEX Track Box testing facility. The latter is a unique 1:1 model of railway track section (of dimensions 21 m ×5 m ×4 m) that has been built to model high-speed rail lines (with passenger and freight trains passing at velocities of up to 400 km/h). The laboratory experiments allowed us to measure the change of stiffness with the fouling level (represented through the void contaminant index, VCI). Numerical simulations are being performed with the Discrete Element Method, reproducing drained triaxial test conditions. Due to the considerable different size of railway ballast and sand grains, we are using idealized packings of spherical particles to study this phenomenon. We are paying particular attention to the sample size effects and are registering the evolution of the stiffness with the fouling level up to high values of VCI. The results obtained from these idealized systems will be contrasted to the laboratory experiments carried out with real railway ballast and sand

Human-robot collaborative multi-agent path planning using Monte Carlo tree search and social reward sources

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe collaboration between humans and robots in an object search task requires the achievement of shared plans obtained from communicating and negotiating. In this work, we assume that the robot computes, as a first step, a multiagent plan for both itself and the human. Then, both plans are submitted to human scrutiny, who either agrees or modifies it forcing the robot to adapt its own restrictions or preferences. This process is repeated along the search task as many times as required by the human. Our planner is based on a decentralized variant of Monte Carlo Tree Search (MCTS), with one robot and one human as agents. Moreover, our algorithm allows the robot and the human to optimize their own actions by maintaining a probability distribution over the plans in a joint action space. The method allows an objective function definition over action sequences, it assumes intermittent communication, it is anytime and suitable for on-line replanning. To test it, we have developed a human-robot communication mobile phone interface. Validation is provided by real-life search experiments of a Parcheesi token in an urban space, including also an acceptability study.Work supported under the Spanish State Research Agency through the Maria de Maeztu Seal of Excellence to IRI (MDM-2016- 0656), ROCOTRANSP project (PID2019-106702RB-C21 / AEI / 10.13039/501100011033), TERRINet (H2020-INFRAIA-2017-1-two-stage730994) and AI4EU (H2020-ICT-2018-2-825619)Peer ReviewedPostprint (published version

Active learning of manipulation sequences

We describe a system allowing a robot to learn goal-directed manipulation sequences such as steps of an assembly task. Learning is based on a free mix of exploration and instruction by an external teacher, and may be active in the sense that the system tests actions to maximize learning progress and asks the teacher if needed. The main component is a symbolic planning engine that operates on learned rules, defined by actions and their pre- and postconditions. Learned by model-based reinforcement learning, rules are immediately available for planning. Thus, there are no distinct learning and application phases. We show how dynamic plans, replanned after every action if necessary, can be used for automatic execution of manipulation sequences, for monitoring of observed manipulation sequences, or a mix of the two, all while extending and refining the rule base on the fly. Quantitative results indicate fast convergence using few training examples, and highly effective teacher intervention at early stages of learning.Peer ReviewedPostprint (author’s final draft

Software tools for the cognitive development of autonomous robots

Research article compendium : peace and conflict researchThe University of Barcelona, in collaboration with different Spanish and foreign institutions and universities, hosted an international workshop on the ‘Sense and Scope of Autonomy in Emerging Military and Security Technologies’, which took place in February 2017. This academic event paved the way to the elaboration of the present report, which contains a compendium of innovative articles written by experts on scientific, legal, diplomatic and military matters. All papers reflect a broad spectrum of views on how ‘autonomy’ can be understood in emerging military and security technologies and what their legal, technical, political and societal impacts are by building on discussions unfolded along a variety of reflective approaches.Peer Reviewe