16 papers
What Matters in RL-Based Methods for Object-Goal Navigation? An Empirical Study and A Unified Framework
Hongze Wang, Boyang Sun, Jiaxu Xing +5
Object-Goal Navigation (ObjectNav) is a key capability for deploying mobile robots in everyday environments such as homes, schools, and workplaces. In this task, an agent must loca…
Learning Agile Quadrotor Flight in the Real World
Yunfan Ren, Zhiyuan Zhu, Jiaxu Xing +1
Learning-based controllers have achieved impressive performance in agile quadrotor flight but typically rely on massive training in simulation, necessitating accurate system identi…
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…
Bridging Performance and Generalization in Reinforcement Learning for Agile Flight
Jonathan Green, Jiaxu Xing, Nico Messikommer +2
Autonomous drone racing is a fundamentally challenging regime for autonomous aerial robots, requiring time-optimal control while operating under persistent actuation saturation. Wh…
Approximate Imitation Learning for Event-based Quadrotor Flight in Cluttered Environments
Nico Messikommer, Jiaxu Xing, Leonard Bauersfeld +3
Event cameras offer high temporal resolution and low latency, making them ideal sensors for high-speed robotic applications where conventional cameras suffer from motion blur. Howe…