290 citations · 1.9k across the 78 of their papers we have counts for
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Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactions
Guanya Shi, Wolfgang Hönig, Xichen Shi +2
We present Neural-Swarm2, a learning-based method for motion planning and control that allows heterogeneous multirotors in a swarm to safely fly in close proximity. Such operation…
Machine Learning Based Path Planning for Improved Rover Navigation (Pre-Print Version)
Neil Abcouwer, Shreyansh Daftry, Siddarth Venkatraman +6
Enhanced AutoNav (ENav), the baseline surface navigation software for NASA's Perseverance rover, sorts a list of candidate paths for the rover to traverse, then uses the Approximat…
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes
Kejun Li, Maegan Tucker, Erdem Bıyık +6
Characterizing what types of exoskeleton gaits are comfortable for users, and understanding the science of walking more generally, require recovering a user's utility landscape. Le…
Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems
Yashwanth Kumar Nakka, Anqi Liu, Guanya Shi +3
Learning-based control algorithms require data collection with abundant supervision for training. Safe exploration algorithms ensure the safety of this data collection process even…
Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions
Guanya Shi, Wolfgang Hönig, Yisong Yue +1
In this paper, we present Neural-Swarm, a nonlinear decentralized stable controller for close-proximity flight of multirotor swarms. Close-proximity control is challenging due to t…
Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits
Maegan Tucker, Myra Cheng, Ellen Novoseller +4
Optimizing lower-body exoskeleton walking gaits for user comfort requires understanding users' preferences over a high-dimensional gait parameter space. However, existing preferenc…
GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning with End-to-End Learning
Benjamin Rivière, Wolfgang Hoenig, Yisong Yue +1
We present GLAS: Global-to-Local Autonomy Synthesis, a provably-safe, automated distributed policy generation for multi-robot motion planning. Our approach combines the advantage o…
Preference-Based Learning for Exoskeleton Gait Optimization
Maegan Tucker, Ellen Novoseller, Claudia Kann +4
This paper presents a personalized gait optimization framework for lower-body exoskeletons. Rather than optimizing numerical objectives such as the mechanical cost of transport, ou…
Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems
Andrew J. Taylor, Victor D. Dorobantu, Hoang M. Le +2
Many modern nonlinear control methods aim to endow systems with guaranteed properties, such as stability or safety, and have been successfully applied to the domain of robotics. Ho…
Neural Lander: Stable Drone Landing Control using Learned Dynamics
Guanya Shi, Xichen Shi, Michael O'Connell +5
Precise near-ground trajectory control is difficult for multi-rotor drones, due to the complex aerodynamic effects caused by interactions between multi-rotor airflow and the enviro…