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5 papers · 1 filter
The More the Merrier: Running Multiple Neuromorphic Components On-Chip for Robotic Control
Evan Eames, Priyadarshini Kannan, Ronan Sangouard +9
It has long been realized that neuromorphic hardware offers benefits for the domain of robotics such as low energy, low latency, as well as unique methods of learning. In aiming fo…
Learning High-Speed Flight in the Wild
Antonio Loquercio, Elia Kaufmann, René Ranftl +3
Quadrotors are agile. Unlike most other machines, they can traverse extremely complex environments at high speeds. To date, only expert human pilots have been able to fully exploit…
Safe Robot Navigation via Multi-Modal Anomaly Detection
Lorenz Wellhausen, René Ranftl, Marco Hutter
Navigation in natural outdoor environments requires a robust and reliable traversability classification method to handle the plethora of situations a robot can encounter. Binary cl…
Learning agile and dynamic motor skills for legged robots
Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy +4
Legged robots pose one of the greatest challenges in robotics. Dynamic and agile maneuvers of animals cannot be imitated by existing methods that are crafted by humans. A compellin…
Frequency-Aware Model Predictive Control
Ruben Grandia, Farbod Farshidian, Alexey Dosovitskiy +2
Transferring solutions found by trajectory optimization to robotic hardware remains a challenging task. When the optimization fully exploits the provided model to perform dynamic t…