Gridbot: An autonomous robot controlled by a Spiking Neural Network mimicking the brain's navigational system

It is true that the "best" neural network is not necessarily the one with the most "brain-like" behavior. Understanding biological intelligence, however, is a fundamental goal for several distinct disciplines. Translating our understanding of intelligence to machines is a fundamental problem in robotics. Propelled by new advancements in Neuroscience, we developed a spiking neural network (SNN) that draws from mounting experimental evidence that a number of individual neurons is associated with spatial navigation. By following the brain's structure, our model assumes no initial all-to-all connectivity, which could inhibit its translation to a neuromorphic hardware, and learns an uncharted territory by mapping its identified components into a limited number of neural representations, through spike-timing dependent plasticity (STDP). In our ongoing effort to employ a bioinspired SNN-controlled robot to real-world spatial mapping applications, we demonstrate here how an SNN may robustly control an autonomous robot in mapping and exploring an unknown environment, while compensating for its own intrinsic hardware imperfections, such as partial or total loss of visual input.Comment: 8 pages, 3 Figures, International Conference on Neuromorphic Systems (ICONS 2018

Selection on non-social traits limits the invasion of social cheats

While the conditions that favour the maintenance of cooperation have been extensively investigated, the significance of non-social selection pressures on social behaviours has received little attention. In the absence of non-social selection pressures, patches of cooperators are vulnerable to invasion by cheats. However, we show both theoretically, and experimentally with the bacterium Pseudomonas fluorescens, that cheats may be unable to invade patches of cooperators under strong non-social selection (both a novel abiotic environment and to a lesser extent, the presence of a virulent parasite). This is because beneficial mutations are most likely to arise in the numerically dominant cooperator population. Given the ubiquity of novel selection pressures on microbes, these results may help to explain why cooperation is the norm in natural populations of microbes

A face recognition system for assistive robots

Assistive robots collaborating with people demand strong Human-Robot interaction capabilities. In this way, recognizing the person the robot has to interact with is paramount to provide a personalized service and reach a satisfactory end-user experience. To this end, face recognition: a non-intrusive, automatic mechanism of identification using biometric identifiers from an user's face, has gained relevance in the recent years, as the advances in machine learning and the creation of huge public datasets have considerably improved the state-of-the-art performance. In this work we study different open-source implementations of the typical components of state-of-the-art face recognition pipelines, including face detection, feature extraction and classification, and propose a recognition system integrating the most suitable methods for their utilization in assistant robots. Concretely, for face detection we have considered MTCNN, OpenCV's DNN, and OpenPose, while for feature extraction we have analyzed InsightFace and Facenet. We have made public an implementation of the proposed recognition framework, ready to be used by any robot running the Robot Operating System (ROS). The methods in the spotlight have been compared in terms of accuracy and performance in common benchmark datasets, namely FDDB and LFW, to aid the choice of the final system implementation, which has been tested in a real robotic platform.This work is supported by the Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech, the research projects WISER ([DPI2017-84827-R]),funded by the Spanish Government, and financed by European RegionalDevelopment’s funds (FEDER), and MoveCare ([ICT-26-2016b-GA-732158]), funded by the European H2020 program, and by a postdoc contract from the I-PPIT-UMA program financed by the University of Málaga

Semi-autonomous human-UAV interfaces for fixed-wing mini-UAVs

Abstract-We present several human-robot interfaces that support real-time control of a small semi-autonomous UAV. These interfaces are designed for searching tasks and other missions that typically do not have a precise predetermined flight plan. We present a detailed analysis of a PDA interface and describe how our other interfaces relate to this analysis. We then offer quantative and qualitative performance comparisons of the interfaces, as well as an analysis of their possible real-world applications

Theory Content, Question-Behavior Effects, or Form of Delivery Effects for Intention to Become an Organ Donor? Two Randomized Trials

Eliciting different attitudes with survey questionnaires may impact on intention to donate organs. Previous research used varying numbers of questionnaire items, or different modes of intervention delivery, when comparing groups. We aimed to determine whether intention to donate organs differed among groups exposed to different theoretical content, but similar questionnaire length, in different countries. We tested the effect of excluding affective attitudinal items on intention to donate, using constant item numbers in two modes of intervention delivery. Study 1: A multi-country, interviewer-led, cross-sectional randomized trial recruited 1007 participants, who completed questionnaires as per group assignment: including all affective attitude items, affective attitude items replaced, negatively-worded affective attitude items replaced. Study 2 recruited a UK-representative, cross-sectional sample of 616 participants using an online methodology, randomly assigned to the same conditions. Multilevel models assessed effects of group membership on outcomes: intention to donate (primary), taking a donor card, following a web-link (secondary). In study 1, intention to donate did not differ among groups. Study 2 found a small, significantly higher intention to donate in the negatively-worded affective attitudes replaced group. Combining data yielded no group differences. No differences were seen for secondary outcomes. Ancillary analyses suggest significant interviewer effects. Contrary to previous research, theoretical content may be less relevant than number or valence of questionnaire items, or form of intervention delivery, for increasing intention to donate organs

Real-World Evolution Adapts Robot Morphology and Control to Hardware Limitations

For robots to handle the numerous factors that can affect them in the real world, they must adapt to changes and unexpected events. Evolutionary robotics tries to solve some of these issues by automatically optimizing a robot for a specific environment. Most of the research in this field, however, uses simplified representations of the robotic system in software simulations. The large gap between performance in simulation and the real world makes it challenging to transfer the resulting robots to the real world. In this paper, we apply real world multi-objective evolutionary optimization to optimize both control and morphology of a four-legged mammal-inspired robot. We change the supply voltage of the system, reducing the available torque and speed of all joints, and study how this affects both the fitness, as well as the morphology and control of the solutions. In addition to demonstrating that this real-world evolutionary scheme for morphology and control is indeed feasible with relatively few evaluations, we show that evolution under the different hardware limitations results in comparable performance for low and moderate speeds, and that the search achieves this by adapting both the control and the morphology of the robot.Comment: Accepted to the 2018 Genetic and Evolutionary Computation Conference (GECCO

Planetary Rover Simulation for Lunar Exploration Missions

When planning planetary rover missions it is useful to develop intuition and skills driving in, quite literally, alien environments before incurring the cost of reaching said locales. Simulators make it possible to operate in environments that have the physical characteristics of target locations without the expense and overhead of extensive physical tests. To that end, NASA Ames and Open Robotics collaborated on a Lunar rover driving simulator based on the open source Gazebo simulation platform and leveraging ROS (Robotic Operating System) components. The simulator was integrated with research and mission software for rover driving, system monitoring, and science instrument simulation to constitute an end-to-end Lunar mission simulation capability. Although we expect our simulator to be applicable to arbitrary Lunar regions, we designed to a reference mission of prospecting in polar regions. The harsh lighting and low illumination angles at the Lunar poles combine with the unique reflectance properties of Lunar regolith to present a challenging visual environment for both human and computer perception. Our simulator placed an emphasis on high fidelity visual simulation in order to produce synthetic imagery suitable for evaluating human rover drivers with navigation tasks, as well as providing test data for computer vision software development.In this paper, we describe the software used to construct the simulated Lunar environment and the components of the driving simulation. Our synthetic terrain generation software artificially increases the resolution of Lunar digital elevation maps by fractal synthesis and inserts craters and rocks based on Lunar size-frequency distribution models. We describe the necessary enhancements to import large scale, high resolution terrains into Gazebo, as well as our approach to modeling the visual environment of the Lunar surface. An overview of the mission software system is provided, along with how ROS was used to emulate flight software components that had not been developed yet. Finally, we discuss the effect of using the high-fidelity synthetic Lunar images for visual odometry. We also characterize the wheel slip model, and find some inconsistencies in the produced wheel slip behaviour