Online adaptation of robot dynamics via function encoders updated with recursive least squares enables real-time model learning from seconds of odometry data and reduces collisions versus static or meta-learning baselines.
Deep-neural-network-based modelling of longitudinal-lateral dynamics to predict the vehicle states for autonomous driving.Sensors, 2022
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Zero to Autonomy in Real-Time: Online Adaptation of Dynamics in Unstructured Environments
Online adaptation of robot dynamics via function encoders updated with recursive least squares enables real-time model learning from seconds of odometry data and reduces collisions versus static or meta-learning baselines.