Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Mattamala, Matias"'
Autor:
Mattamala, Matías, Chebrolu, Nived, Casseau, Benoit, Freißmuth, Leonard, Frey, Jonas, Tuna, Turcan, Hutter, Marco, Fallon, Maurice
We present a solution for autonomous forest inventory with a legged robotic platform. Compared to their wheeled and aerial counterparts, legged platforms offer an attractive balance of endurance and low soil impact for forest applications. In this pa
Externí odkaz:
http://arxiv.org/abs/2404.14157
Autor:
Mattamala, Matías, Frey, Jonas, Libera, Piotr, Chebrolu, Nived, Martius, Georg, Cadena, Cesar, Hutter, Marco, Fallon, Maurice
Natural environments such as forests and grasslands are challenging for robotic navigation because of the false perception of rigid obstacles from high grass, twigs, or bushes. In this work, we present Wild Visual Navigation (WVN), an online self-sup
Externí odkaz:
http://arxiv.org/abs/2404.07110
Autor:
Freißmuth, Leonard, Mattamala, Matias, Chebrolu, Nived, Schaefer, Simon, Leutenegger, Stefan, Fallon, Maurice
Terrestrial laser scanning (TLS) is the standard technique used to create accurate point clouds for digital forest inventories. However, the measurement process is demanding, requiring up to two days per hectare for data collection, significant data
Externí odkaz:
http://arxiv.org/abs/2403.17622
Many LiDAR place recognition systems have been developed and tested specifically for urban driving scenarios. Their performance in natural environments such as forests and woodlands have been studied less closely. In this paper, we analyzed the capab
Externí odkaz:
http://arxiv.org/abs/2403.14326
Exoskeletons for daily use by those with mobility impairments are being developed. They will require accurate and robust scene understanding systems. Current research has used vision to identify immediate terrain and geometric obstacles, however thes
Externí odkaz:
http://arxiv.org/abs/2403.14320
Autor:
Tao, Yifu, Bhalgat, Yash, Fu, Lanke Frank Tarimo, Mattamala, Matias, Chebrolu, Nived, Fallon, Maurice
We present a neural-field-based large-scale reconstruction system that fuses lidar and vision data to generate high-quality reconstructions that are geometrically accurate and capture photo-realistic textures. This system adapts the state-of-the-art
Externí odkaz:
http://arxiv.org/abs/2403.06877
Autor:
Jin, Jin, Zhang, Chong, Frey, Jonas, Rudin, Nikita, Mattamala, Matias, Cadena, Cesar, Hutter, Marco
Autonomous robots must navigate reliably in unknown environments even under compromised exteroceptive perception, or perception failures. Such failures often occur when harsh environments lead to degraded sensing, or when the perception algorithm mis
Externí odkaz:
http://arxiv.org/abs/2310.03581
Elevation maps are commonly used to represent the environment of mobile robots and are instrumental for locomotion and navigation tasks. However, pure geometric information is insufficient for many field applications that require appearance or semant
Externí odkaz:
http://arxiv.org/abs/2309.16818
Versatile and adaptive semantic understanding would enable autonomous systems to comprehend and interact with their surroundings. Existing fixed-class models limit the adaptability of indoor mobile and assistive autonomous systems. In this work, we i
Externí odkaz:
http://arxiv.org/abs/2309.15065
Autor:
Frey, Jonas, Mattamala, Matias, Chebrolu, Nived, Cadena, Cesar, Fallon, Maurice, Hutter, Marco
Natural environments such as forests and grasslands are challenging for robotic navigation because of the false perception of rigid obstacles from high grass, twigs, or bushes. In this work, we propose Wild Visual Navigation (WVN), an online self-sup
Externí odkaz:
http://arxiv.org/abs/2305.08510