7 papers
Physics-Aware Sparse Learning and Selective Online Adaptation for Euler-Lagrange Robot Dynamics
Rishabh Dev Yadav, Samaksh Ujjawal, Sihao Sun +2
Accurate dynamics models are essential for model-based robotic control, yet nominal Euler--Lagrange models often become inaccurate in the presence of payload variation, unmodeled c…
Strategizing at Speed: A Learned Model Predictive Game for Multi-Agent Drone Racing
Andrei-Carlo Papuc, Lasse Peters, Sihao Sun +2
Autonomous drone racing pushes the boundaries of high-speed motion planning and multi-agent strategic decision-making. Success in this domain requires drones not only to navigate a…
Learning Cross-Coupled and Regime Dependent Dynamics for Aerial Manipulation
Rishabh Dev Yadav, Samaksh Ujjawal, Sihao Sun +2
Accurate dynamics models are critical for aerial manipulators operating under complex tasks such as payload transport. However, modeling these systems remains fundamentally challen…
Global End-Effector Pose Control of an Underactuated Aerial Manipulator via Reinforcement Learning
Shlok Deshmukh, Javier Alonso-Mora, Sihao Sun
Aerial manipulators, which combine robotic arms with multi-rotor drones, face strict constraints on arm weight and mechanical complexity. In this work, we study a lightweight 2-deg…
Decentralized Aerial Manipulation of a Cable-Suspended Load using Multi-Agent Reinforcement Learning
Jack Zeng, Andreu Matoses Gimenez, Eugene Vinitsky +2
This paper presents the first decentralized method to enable real-world 6-DoF manipulation of a cable-suspended load using a team of Micro-Aerial Vehicles (MAVs). Our method levera…
Agile and Cooperative Aerial Manipulation of a Cable-Suspended Load
Sihao Sun, Xuerui Wang, Dario Sanalitro +3
Quadrotors can carry slung loads to hard-to-reach locations at high speed. Since a single quadrotor has limited payload capacities, using a team of quadrotors to collaboratively ma…