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Let the Dynamics Flow: Stable Flow Matching Dynamical Systems
Rodrigo Pérez-Dattari, Francisco Leiva, Andrea Testa +3
Flow matching has recently emerged as a powerful approach for imitation learning, enabling scalable, expressive, and multimodal motion policies. However, when modeling these polici…
PEBRE: An Open-Hardware Compute and Perception Add-On for the Pepper Robot
Malte Kuhlmann, Ignacio Bugueno-Cordova, Emil Alms +2
This paper presents the design, development, and experimental verification of PEBRE, an open-hardware add-on for fast software development on the Pepper Robot. Our project enhances…
Sem-NaVAE: Semantically-Guided Outdoor Mapless Navigation via Generative Trajectory Priors
Gonzalo Olguín, Javier Ruiz-del-Solar
This work presents a mapless navigation approach for outdoor applications. It combines the exploratory capacity of conditional variational autoencoders (CVAEs) to generate trajecto…
Data-driven control of hydraulic impact hammers under strict operational and control constraints
Francisco Leiva, Claudio Canales, Michelle Valenzuela +1
This paper presents a data-driven methodology for the control of static hydraulic impact hammers, also known as rock breakers, which are commonly used in the mining industry. The t…
Autonomous loading of ore piles with Load-Haul-Dump machines using Deep Reinforcement Learning
Rodrigo Salas, Francisco Leiva, Javier Ruiz-del-Solar
This work presents a deep reinforcement learning-based approach to train controllers for the autonomous loading of ore piles with a Load-Haul-Dump (LHD) machine. These controllers…
Combining RL and IL using a dynamic, performance-based modulation over learning signals and its application to local planning
Francisco Leiva, Javier Ruiz-del-Solar
This paper proposes a method to combine reinforcement learning (RL) and imitation learning (IL) using a dynamic, performance-based modulation over learning signals. The proposed me…