Mavrl: Learn to fly in cluttered environments with varying speed
Autonomous flight in unknown, cluttered environments is still a major challenge in robotics.
Existing obstacle avoidance algorithms typically adopt a fixed flight velocity, overlooking the …
Existing obstacle avoidance algorithms typically adopt a fixed flight velocity, overlooking the …
Reinforcement learning for collision-free flight exploiting deep collision encoding
M Kulkarni, K Alexis - ar** Drones for Swift Movement and Reliable Precision via Deep Learning
G Del Col - 2024 - aaltodoc.aalto.fi
As the demand for autonomous map** flights in forest environments grows, the need for
efficient and reliable quadrotor technologies becomes clear. This thesis, conducted at the …
efficient and reliable quadrotor technologies becomes clear. This thesis, conducted at the …
A Framework to Allow Unmanned Aerial Vehicles to Make Good Collisions
M Molnar - 2024 - search.proquest.com
The field of unmanned aerial vehicle, or UAV, navigation has been moving towards collision
inclusive path planning, yet work has not been done to consider what a UAV is colliding …
inclusive path planning, yet work has not been done to consider what a UAV is colliding …
Multi-modal Learning-based Navigation
AE Øren - 2024 - ntnuopen.ntnu.no
In denne oppgaven utforskes kollisjonsunngåelse i et skogsmiljø. Spesielt fokuseres det på
effektene av å integrere en sekundærmodalitet ved å utvide en variasjonell autoenkoder …
effektene av å integrere en sekundærmodalitet ved å utvide en variasjonell autoenkoder …
[PDF][PDF] ARL Educational Robotic Autonomy Environment–v0.
This document outlines the ARL Educational Robotic Autonomy Environment v0. 1 (ARL-
Edu v0. 1) which solely relies on open-source projects of our lab and of the community. ARL …
Edu v0. 1) which solely relies on open-source projects of our lab and of the community. ARL …