69 citations · 462 across the 66 of their papers we have counts for
8 papers · 2 filters
Differential Flatness and Flatness Inspired Control of Aerial Manipulators based on Lagrangian Reduction
Skylar X. Wei, Peder Harderup, Joel Burdick
This paper shows that the dynamics of a general class of aerial manipulators, consist of an underactuated multi-rotor base with an arbitrary k-linked articulated manipulator, are d…
Quadrotor Trajectory Tracking with Learned Dynamics: Joint Koopman-based Learning of System Models and Function Dictionaries
Carl Folkestad, Skylar X. Wei, Joel W. Burdick
Nonlinear dynamical effects are crucial to the operation of many agile robotic systems. Koopman-based model learning methods can capture these nonlinear dynamical system effects in…
Koopman NMPC: Koopman-based Learning and Nonlinear Model Predictive Control of Control-affine Systems
Carl Folkestad, Joel W. Burdick
Koopman-based learning methods can potentially be practical and powerful tools for dynamical robotic systems. However, common methods to construct Koopman representations seek to l…
Limits of Probabilistic Safety Guarantees when Considering Human Uncertainty
Richard Cheng, Richard M. Murray, Joel W. Burdick
When autonomous robots interact with humans, such as during autonomous driving, explicit safety guarantees are crucial in order to avoid potentially life-threatening accidents. Man…
NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge
Ali Agha, Kyohei Otsu, Benjamin Morrell +69
This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARP…
STEP: Stochastic Traversability Evaluation and Planning for Risk-Aware Off-road Navigation
David D. Fan, Kyohei Otsu, Yuki Kubo +3
Although ground robotic autonomy has gained widespread usage in structured and controlled environments, autonomy in unknown and off-road terrain remains a difficult problem. Extrem…