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Federico Paredes-Vallés

5 accepted papers

2024

Lightweight Event-based Optical Flow Estimation via Iterative Deblurring

ICRA 2024poster

Inspired by frame-based methods, state-of-the-art event-based optical flow networks rely on the explicit construction of correlation volumes, which are expensive to compute and store, rendering them unsuitable for robotic applications with limited compute and energy budget. Moreover, correlation vol…

Cited by 21SourcecodeScholar
2023

NanoFlowNet: Real-time Dense Optical Flow on a Nano Quadcopter

ICRA 2023poster

Nano quadcopters are small, agile, and cheap platforms that are well suited for deployment in narrow, cluttered environments. Due to their limited payload, these vehicles are highly constrained in processing power, rendering conventional vision-based methods for safe and autonomous navigation incomp…

Cited by 23SourceScholar
2023

Taming Contrast Maximization for Learning Sequential, Low-latency, Event-based Optical Flow

ICCV 2023poster

Event cameras have recently gained significant traction since they open up new avenues for low-latency and low-power solutions to complex computer vision problems. To unlock these solutions, it is necessary to develop algorithms that can leverage the unique nature of event data. However, the current…

Cited by 25PDFScholar
2021

Neuromorphic control for optic-flow-based landing of MAVs using the Loihi processor

ICRA 2021poster

Neuromorphic processors like Loihi offer a promising alternative to conventional computing modules for endowing constrained systems like micro air vehicles (MAVs) with robust, efficient and autonomous skills such as take-off and landing, obstacle avoidance, and pursuit. However, a major challenge fo…

Cited by 59SourceScholar
2020

Evolved Neuromorphic Control for High Speed Divergence-Based Landings of MAVs

RA-L 2020

Flying insects are capable of vision-based navigation in cluttered environments, reliably avoiding obstacles through fast and agile maneuvers, while being very efficient in the processing of visual stimuli. Meanwhile, autonomous micro air vehicles still lag far behind their biological counterparts,

Cited by 24SourcecodeScholar