Guiding the Exploration of the Solution Space in Walking Robots Through Growth-Based Morphological Development

In human beings, the joint development of the body and cognitive system has been shown to facilitate the acquisition of new skills and abilities. In the literature, these natural principles have been applied to robotics with mixed results and different authors have suggested several hypotheses to explain them. One of the most popular hypotheses states that morphological development improves learning by increasing exploration of the solution space, avoiding stagnation in local optima. In this article, we are going to study the influence of growth-based morphological development and its nuances as a tool to improve the exploration of the solution space. We will perform a series of experiments over two different robot morphologies which learn to walk. Furthermore, we will compare these results to another optimization strategy that has been shown to be useful to favor exploration in learning algorithms: the application of noise during learning. Finally, to check if the increased exploration hypothesis holds, we visualize the genotypic space during learning considering the different optimization strategies by using the Search Trajectory Network representation. The results indicate that noise and growth increase exploration, but only growth guides the search towards good solutions

An Experiment in Morphological Development for Learning ANN Based Controllers

Morphological development is part of the way any human or animal learns. The learning processes starts with the morphology at birth and progresses through changing morphologies until adulthood is reached. Biologically, this seems to facilitate learning and make it more robust. However, when this approach is transferred to robotic systems, the results found in the literature are inconsistent: morphological development does not provide a learning advantage in every case. In fact, it can lead to poorer results than when learning with a fixed morphology. In this paper we analyze some of the issues involved by means of a simple, but very informative experiment in quadruped walking. From the results obtained an initial series of insights on when and under what conditions to apply morphological development for learning are presented.Comment: 10 pages, 4 figures. arXiv admin note: text overlap with arXiv:2003.0581

Engineering Morphological Development in a Robotic Bipedal Walking Problem: An Empirical Study

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract]: In living beings, the natural development of the body has been shown to facilitate learning. The application of these natural developmental principles in robotics have been considered in different robotic morphologies and scenarios, leading to mixed results. Development was found to be beneficial for learning in some instances, but also irrelevant or detrimental in others. This mix of results and scenarios has allowed researchers to extract some notions about the conditions that must be fulfilled or set to apply morphological development successfully. Notions that we have organized to set a series of design conditions to successfully apply morphological development. Thus, in this article, we are going to focus on the study of one of them that has been frequently addressed by researchers in their studies in very general terms. It can be described as the need to achieve a suitable synergy among the different components involved in the development and learning process: morphological development strategy, controller, task, and learning algorithm. In particular, we have concentrated on empirically determining the influence of five developmental strategies, implemented in different ways, applied at different speeds and deployed in different orders and combinations, over the problem of a NAO robot controlled by an artificial neural network obtained through a neuroevolutionary algorithm learning a bipedal walking task. The results obtained permit providing a more detailed description of what a suitable synergy implies and how it can be utilized to design more successful morphological developmental processes to improve robot learning.Xunta de Galicia ; EDC431C-2021/39Research supported by the European Commission Horizon program PILLAR-Robots project, grant 101070381, the Xunta de Galicia and the European Regional Development Funds under grant EDC431C-2021/39 and the Spanish Science and Education Ministry through grant PID2021-126220OB-100. We wish to acknowledge the support received from the Centro de Investigación de Galicia ‘‘CITIC”, funded by Xunta de Galicia and the European Union (European Regional Development Fund-Galicia 2014-2020 Program), by grant ED431G 2019/01 and the Centro de Supercomputación de Galicia (CESGA)Xunta de Galicia; ED431G 2019/0

Advanced Silicon Avalanche Photodiodes on NASA's Global Ecosystem Dynamics Investigation (GEDI) Mission

Silicon Avalanche Photodiodes (APDs) are used in NASAs Global Ecosystem Dynamics Investigation (GEDI) which was launched in December 2018 and is currently measuring the Earths vegetation vertical structure from the International Space Station. The APDs were specially made for space lidar with a much lower hole-to-electron ionization coefficient ratio (k-factor ~0.008) than that of commercially available silicon APDs in order to reduce the APD excess noise from the randomness of the avalanche gain. A silicon heater resistor was used under the APD chip to heat the device up to 70C and improve its quantum efficiency at 1064 nm laser wavelength while maintaining a low dark current such that the overall signal to noise ratio is improved. Special APD protection circuits were used to raise the overload damage threshold to prevent device damage from strong laser return by specular surfaces, such as still water bodies, and space radiation events. The APD and a hybrid transimpedance amplifier circuit were hermetically sealed in a package with a sufficiently low leak rate to ensure multi-year operation lifetime in space. The detector assemblies underwent a series of pre-launch tests per NASA Goddard Environmental Verification Standard for space qualification. They have performed exactly as expected with GEDI in orbit. A detailed description of the GEDI detector design, signal and noise model, and test results are presented in this paper