LEONARDO: a bipedal walking robot that can fly, slackline, and skateboard

MAGIC-VFM Meta-learning Adaptation for Ground Interaction Control with Visual Foundation Models

Learning-based Minimally-Sensed Fault-Tolerant Adaptive Flight Control for Flying Cars

Trajectory Optimization of Chance-Constrained Nonlinear Stochastic Systems for Motion Planning

Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds

Neural Tree Expansion for Multi-Robot Planning in Non-Cooperative Environments

LEONARDO: a bipedal walking robot that can fly, slackline, and skateboard

Neural Tree Expansion for Multi-Robot Planning (updated video: https://youtu.be/tkmTYUWnAOw)

Information-Based Guidance and Control of Spacecraft for Autonomous Inspection

Happy Holidays from the LEONARDO robot by Caltech's Aerospace Robotics and Control Lab

Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactions

GLAS (Global-to-Local Autonomy Synthesis) for Multi-Robot Motion Planning with End-to-End Learning

Adaptive Flight Control of a Flying Car Model (VTOL with Wings) using Airflow Vector Sensing