36 citations · 38 across the 5 of their papers we have counts for
5 papers
Perception-Aware Autonomous Exploration in Feature-Limited Environments
Moji Shi, Rajitha de Silva, Hang Yu +2
Autonomous exploration in unknown environments typically relies on onboard state estimation for localisation and mapping. Existing exploration methods primarily maximise coverage e…
Depth Transfer: Learning to See Like a Simulator for Real-World Drone Navigation
Hang Yu, Christophe De Wagter, Guido C. H. E de Croon
Sim-to-real transfer is a fundamental challenge in robot reinforcement learning. Discrepancies between simulation and reality can significantly impair policy performance, especiall…
MAVRL: Learn to Fly in Cluttered Environments with Varying Speed
Hang Yu, Christophe De Wagter, Guido C. H. E de Croon
Many existing obstacle avoidance algorithms overlook the crucial balance between safety and agility, especially in environments of varying complexity. In our study, we introduce an…
AvoidBench: A high-fidelity vision-based obstacle avoidance benchmarking suite for multi-rotors
Hang Yu, Guido C. H. E de Croon, Christophe De Wagter
Obstacle avoidance is an essential topic in the field of autonomous drone research. When choosing an avoidance algorithm, many different options are available, each with their adva…
AP-10K: A Benchmark for Animal Pose Estimation in the Wild
Hang Yu, Yufei Xu, Jing Zhang +3
Accurate animal pose estimation is an essential step towards understanding animal behavior, and can potentially benefit many downstream applications, such as wildlife conservation.…