3 accepted papers
In pose estimation for seen objects, a prevalent pipeline involves using neural networks to predict dense 3D coordinates of the object surface on 2D images, which are then used to establish dense 2D-3D correspondences. However, current methods primarily focus on more efficient encoding techniques to…
Legged aerial-terrestrial robots have garnered significant research attention in recent years due to their enhanced environmental adaptability through combined aerial and terrestrial locomotion. However, existing passive spring-legged aerial robots exhibit limited motion versatility, demonstrating s
Quadrotors, while versatile, are vulnerable to unpredictable environmental disturbances, including turbulence, gusts, and ground effects, making precise path-following control a formidable challenge. This letter introduces an adaptive neural network-based predictive control framework tailored for qu