3,029 research outputs found
Embodied Evolution in Collective Robotics: A Review
This paper provides an overview of evolutionary robotics techniques applied
to on-line distributed evolution for robot collectives -- namely, embodied
evolution. It provides a definition of embodied evolution as well as a thorough
description of the underlying concepts and mechanisms. The paper also presents
a comprehensive summary of research published in the field since its inception
(1999-2017), providing various perspectives to identify the major trends. In
particular, we identify a shift from considering embodied evolution as a
parallel search method within small robot collectives (fewer than 10 robots) to
embodied evolution as an on-line distributed learning method for designing
collective behaviours in swarm-like collectives. The paper concludes with a
discussion of applications and open questions, providing a milestone for past
and an inspiration for future research.Comment: 23 pages, 1 figure, 1 tabl
Artificial in its own right
Artificial Cells, , Artificial Ecologies, Artificial Intelligence, Bio-Inspired Hardware Systems, Computational Autopoiesis, Computational Biology, Computational Embryology, Computational Evolution, Morphogenesis, Cyborgization, Digital Evolution, Evolvable Hardware, Cyborgs, Mathematical Biology, Nanotechnology, Posthuman, Transhuman
Lighthouses and Global Graph Stabilization: Active SLAM for Low-compute, Narrow-FoV Robots
Autonomous exploration to build a map of an unknown environment is a
fundamental robotics problem. However, the quality of the map directly
influences the quality of subsequent robot operation. Instability in a
simultaneous localization and mapping (SLAM) system can lead to poorquality
maps and subsequent navigation failures during or after exploration. This
becomes particularly noticeable in consumer robotics, where compute budget and
limited field-of-view are very common. In this work, we propose (i) the concept
of lighthouses: panoramic views with high visual information content that can
be used to maintain the stability of the map locally in their neighborhoods and
(ii) the final stabilization strategy for global pose graph stabilization. We
call our novel exploration strategy SLAM-aware exploration (SAE) and evaluate
its performance on real-world home environments.Comment: 7 pages, 7 figure
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