Fernando Cladera Ojeda — accepted AI-conference papers

2022

EV-Catcher: High-Speed Object Catching Using Low-Latency Event-Based Neural Networks

Ziyun Wang, Fernando Cladera Ojeda, Anthony Bisulco, Daewon Lee, Camillo J. Taylor, Kostas Daniilidis +3

RA-L 2022

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 real-time perception tasks in highly dynamic enviro

Cited by 26 Source ↗Scholar ↗

2022

Large-Scale Autonomous Flight With Real-Time Semantic SLAM Under Dense Forest Canopy

Xu Liu, Guilherme V. Nardari, Fernando Cladera Ojeda, Yuezhan Tao, Alex Zhou, Thomas Donnelly +5

RA-L 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 information in highly unstructured, GPS-denied environments

Cited by 99 Source ↗Scholar ↗

2022

Stronger Together: Air-Ground Robotic Collaboration Using Semantics

Ian D. Miller, Fernando Cladera Ojeda, Trey Smith, Camillo Jose Taylor, Vijay Kumar

RA-L 2022

In this work, we present an end-to-end heterogeneous multi-robot system framework where ground robots are able to localize, plan, and navigate in a semantic map created in real time by a high-altitude quadrotor. The ground robots choose and deconflict their targets independently, without any externa

Cited by 54 Source ↗code ↗Scholar ↗

2020

Mine Tunnel Exploration Using Multiple Quadrupedal Robots

Ian D. Miller, Avraham Cohen, Adarsh Kulkarni, James Laney, Camillo Jose Taylor, Vijay Kumar +8

RA-L 2020

Robotic exploration of underground environments is a particularly challenging problem due to communication, endurance, and traversability constraints which necessitate high degrees of autonomy and agility. These challenges are further exacerbated by the need to minimize human intervention for practi

Cited by 108 Source ↗Scholar ↗