2 citations · 2 across the 7 of their papers we have counts for
8 papers
Learning to Throw: Agile and Accurate Cable-Suspended Payload Delivery with a Quadrotor
Yifan Zhai, Elia Raimondi, Yunfan Ren +4
Quadrotors offer the agility needed to rapidly transport suspended payloads during time-critical applications, including search-and-rescue and medical delivery. While suspended-pay…
Continual Robot Policy Learning via Variational Neural Dynamics
Jiaxu Xing, Zhiyuan Zhu, Yunfan Ren +4
Robots deployed in the real world rarely operate under a single fixed dynamics model: wind changes, payloads vary, batteries drain, contacts shift, and hardware wears. Yet most lea…
Superhuman Safe and Agile Racing through Multi-Agent Reinforcement Learning
Ismail Geles, Leonard Bauersfeld, Markus Wulfmeier +1
Autonomous systems have achieved superhuman performance in isolation or simulation, yet they remain brittle in shared, dynamic real-world spaces. This failure stems from the domina…
Learning Acrobatic Flight from Preferences
Colin Merk, Ismail Geles, Jiaxu Xing +3
Preference-based reinforcement learning (PbRL) enables agents to learn control policies without requiring manually designed reward functions, making it well-suited for tasks where…
Dream to Fly: Model-Based Reinforcement Learning for Vision-Based Drone Flight
Angel Romero, Ashwin Shenai, Ismail Geles +2
Autonomous drone racing has risen as a challenging robotic benchmark for testing the limits of learning, perception, planning, and control. Expert human pilots are able to fly a dr…
Multi-Task Reinforcement Learning for Quadrotors
Jiaxu Xing, Ismail Geles, Yunlong Song +2
Reinforcement learning (RL) has shown great effectiveness in quadrotor control, enabling specialized policies to develop even human-champion-level performance in single-task scenar…
Demonstrating Agile Flight from Pixels without State Estimation
Ismail Geles, Leonard Bauersfeld, Angel Romero +2
Quadrotors are among the most agile flying robots. Despite recent advances in learning-based control and computer vision, autonomous drones still rely on explicit state estimation.…
Learning to Open Doors with an Aerial Manipulator
Eugenio Cuniato, Ismail Geles, Weixuan Zhang +3
The field of aerial manipulation has seen rapid advances, transitioning from push-and-slide tasks to interaction with articulated objects. So far, when more complex actions are per…