Evolving hexacopter morphologies together with learnable controllers produces unconventional drones that outperform standard designs on complex tasks while introducing new metrics for evolution-learning interactions.
IEEE Transactions on Cognitive and Developmental Systems15(2), 507–517 (2023)
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An open-sourced Unified Autonomy Stack fuses LiDAR, radar, vision and inertial data with sampling-based planning and control barrier functions to deliver resilient autonomy on aerial and ground robots in challenging real-world settings.
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Unconventional Hexacopters via Evolution and Learning: Performance Gains and New Insights
Evolving hexacopter morphologies together with learnable controllers produces unconventional drones that outperform standard designs on complex tasks while introducing new metrics for evolution-learning interactions.
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The Unified Autonomy Stack: Toward a Blueprint for Generalizable Robot Autonomy
An open-sourced Unified Autonomy Stack fuses LiDAR, radar, vision and inertial data with sampling-based planning and control barrier functions to deliver resilient autonomy on aerial and ground robots in challenging real-world settings.