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Yu Fan Chen

7 accepted papers

2022

FireFly: An Insect-Scale Aerial Robot Powered by Electroluminescent Soft Artificial Muscles

RA-L 2022

Light production in natural fireflies represents an effective and unique method for communication and mating. Inspired by bioluminescence, we develop a 650 mg aerial robot powered by four electroluminescent (EL) dielectric elastomer actuators (DEAs) that have distinct colors and patterns. To enable

Cited by 10SourceScholar
2018

Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning

IROS 2018poster

Robots that navigate among pedestrians use collision avoidance algorithms to enable safe and efficient operation. Recent works present deep reinforcement learning as a framework to model the complex interactions and cooperation. However, they are implemented using key assumptions about other agents'…

Cited by 652SourcecodeScholar
2017

Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning

ICRA 2017poster

Finding feasible, collision-free paths for multiagent systems can be challenging, particularly in non-communicating scenarios where each agent's intent (e.g. goal) is unobservable to the others. In particular, finding time efficient paths often requires anticipating interaction with neighboring agen…

Cited by 834SourceScholar
2017

Duckietown: An open, inexpensive and flexible platform for autonomy education and research

ICRA 2017poster

Duckietown is an open, inexpensive and flexible platform for autonomy education and research. The platform comprises small autonomous vehicles (“Duckiebots”) built from off-the-shelf components, and cities (“Duckietowns”) complete with roads, signage, traffic lights, obstacles, and citizens (duckies…

Cited by 281SourceScholar
2017

Socially aware motion planning with deep reinforcement learning

IROS 2017poster

For robotic vehicles to navigate safely and efficiently in pedestrian-rich environments, it is important to model subtle human behaviors and navigation rules (e.g., passing on the right). However, while instinctive to humans, socially compliant navigation is still difficult to quantify due to the st…

Cited by 888SourceScholar