Výsledky vyhledávání - "Fernando Cladera"

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Towards Understanding Underwater Weather Events in Rivers Using Autonomous Surface Vehicles

Autor: Li, Alice K., Mao, Yue, Manjanna, Sandeep, Liu, Sixuan, Dhanoa, Jasleen, Mehta, Bharg, Edwards, Victoria M., Ojeda, Fernando Cladera, Men, Maël Le, Sigg, Eric, Ulloa, Hugo N., Jerolmack, Douglas J., Hsieh, M. Ani

Climate change has increased the frequency and severity of extreme weather events such as hurricanes and winter storms. The complex interplay of floods with tides, runoff, and sediment creates additional hazards -- including erosion and the undermini

Externí odkaz: http://arxiv.org/abs/2312.14248

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TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards

Autor: Cheng, Derek, Ojeda, Fernando Cladera, Prabhu, Ankit, Liu, Xu, Zhu, Alan, Green, Patrick Corey, Ehsani, Reza, Chaudhari, Pratik, Kumar, Vijay

Data collection for forestry, timber, and agriculture currently relies on manual techniques which are labor-intensive and time-consuming. We seek to demonstrate that robotics offers improvements over these techniques and accelerate agricultural resea

Externí odkaz: http://arxiv.org/abs/2310.02162

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EV-Catcher: High-Speed Object Catching Using Low-latency Event-based Neural Networks

Autor: Wang, Ziyun, Ojeda, Fernando Cladera, Bisulco, Anthony, Lee, Daewon, Taylor, Camillo J., Daniilidis, Kostas, Hsieh, M. Ani, Lee, Daniel D., Isler, Volkan

Event-based sensors have recently drawn increasing interest in robotic perception due to their lower latency, higher dynamic range, and lower bandwidth requirements compared to standard CMOS-based imagers. These properties make them ideal tools for r

Externí odkaz: http://arxiv.org/abs/2304.07200

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Large-scale Autonomous Flight with Real-time Semantic SLAM under Dense Forest Canopy

Autor: Liu, Xu, Nardari, Guilherme V., Ojeda, Fernando Cladera, Tao, Yuezhan, Zhou, Alex, Donnelly, Thomas, Qu, Chao, Chen, Steven W., Romero, Roseli A. F., Taylor, Camillo J., Kumar, Vijay

Publikováno v: IEEE Robotics and Automation Letters ( Volume: 7, Issue: 2, April 2022)

Semantic maps represent the environment using a set of semantically meaningful objects. This representation is storage-efficient, less ambiguous, and more informative, thus facilitating large-scale autonomy and the acquisition of actionable informati

Externí odkaz: http://arxiv.org/abs/2109.06479

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Fast Motion Understanding with Spatiotemporal Neural Networks and Dynamic Vision Sensors

Autor: Bisulco, Anthony, Ojeda, Fernando Cladera, Isler, Volkan, Lee, Daniel D.

Publikováno v: International Conference on Robotics and Automation (ICRA) 2021

This paper presents a Dynamic Vision Sensor (DVS) based system for reasoning about high speed motion. As a representative scenario, we consider the case of a robot at rest reacting to a small, fast approaching object at speeds higher than 15m/s. Sinc

Externí odkaz: http://arxiv.org/abs/2011.09427

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Near-chip Dynamic Vision Filtering for Low-Bandwidth Pedestrian Detection

Autor: Bisulco, Anthony, Ojeda, Fernando Cladera, Isler, Volkan, Lee, Daniel D.

This paper presents a novel end-to-end system for pedestrian detection using Dynamic Vision Sensors (DVSs). We target applications where multiple sensors transmit data to a local processing unit, which executes a detection algorithm. Our system is co

Externí odkaz: http://arxiv.org/abs/2004.01689

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