Zobrazeno 1 - 10
of 272
pro vyhledávání: '"Song, Yunlong"'
Autor:
Hu, Yu, Zhang, Yuang, Song, Yunlong, Deng, Yang, Yu, Feng, Zhang, Linzuo, Lin, Weiyao, Zou, Danping, Yu, Wenxian
Optical flow captures the motion of pixels in an image sequence over time, providing information about movement, depth, and environmental structure. Flying insects utilize this information to navigate and avoid obstacles, allowing them to execute hig
Externí odkaz:
http://arxiv.org/abs/2411.04413
The sample inefficiency of reinforcement learning (RL) remains a significant challenge in robotics. RL requires large-scale simulation and, still, can cause long training times, slowing down research and innovation. This issue is particularly pronoun
Externí odkaz:
http://arxiv.org/abs/2410.15979
First-order Policy Gradient (FoPG) algorithms such as Backpropagation through Time and Analytical Policy Gradients leverage local simulation physics to accelerate policy search, significantly improving sample efficiency in robot control compared to s
Externí odkaz:
http://arxiv.org/abs/2410.03076
Swarm navigation in cluttered environments is a grand challenge in robotics. This work combines deep learning with first-principle physics through differentiable simulation to enable autonomous navigation of multiple aerial robots through complex env
Externí odkaz:
http://arxiv.org/abs/2407.10648
Autor:
Song, Yunlong, Scaramuzza, Davide
Control systems are at the core of every real-world robot. They are deployed in an ever-increasing number of applications, ranging from autonomous racing and search-and-rescue missions to industrial inspections and space exploration. To achieve peak
Externí odkaz:
http://arxiv.org/abs/2407.01568
This work explores the potential of using differentiable simulation for learning quadruped locomotion. Differentiable simulation promises fast convergence and stable training by computing low-variance first-order gradients using robot dynamics. Howev
Externí odkaz:
http://arxiv.org/abs/2403.14864
Autor:
Song, Yunlong, Scaramuzza, Davide
Trajectory visualization and animation play critical roles in robotics research. However, existing data visualization and animation tools often lack flexibility, scalability, and versatility, resulting in limited capability to fully explore and analy
Externí odkaz:
http://arxiv.org/abs/2310.11659
Publikováno v:
Science Robotics, 2023
A central question in robotics is how to design a control system for an agile mobile robot. This paper studies this question systematically, focusing on a challenging setting: autonomous drone racing. We show that a neural network controller trained
Externí odkaz:
http://arxiv.org/abs/2310.10943
Autor:
L'Erario, Giuseppe, Hanover, Drew, Romero, Angel, Song, Yunlong, Nava, Gabriele, Viceconte, Paolo Maria, Pucci, Daniele, Scaramuzza, Davide
Robot multimodal locomotion encompasses the ability to transition between walking and flying, representing a significant challenge in robotics. This work presents an approach that enables automatic smooth transitions between legged and aerial locomot
Externí odkaz:
http://arxiv.org/abs/2309.12784
Publikováno v:
IEEE International Conference on Robotics and Automation (ICRA), 2024
Scene transfer for vision-based mobile robotics applications is a highly relevant and challenging problem. The utility of a robot greatly depends on its ability to perform a task in the real world, outside of a well-controlled lab environment. Existi
Externí odkaz:
http://arxiv.org/abs/2309.09865