10 citations · 12 across the 8 of their papers we have counts for
12 papers
An Addendum to NeBula: Towards Extending TEAM CoSTAR's Solution to Larger Scale Environments
Ali Agha, Kyohei Otsu, Benjamin Morrell +86
This paper presents an appendix to the original NeBula autonomy solution developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), participating in the DARPA Sub…
Borinot: an open thrust-torque-controlled robot for research on agile aerial-contact motion
Josep Martí-Saumell, Hugo Duarte, Patrick Grosch +3
This paper introduces Borinot, an open-source aerial robotic platform designed to conduct research on hybrid agile locomotion and manipulation using flight and contacts. This platf…
Borinot: an agile torque-controlled robot for hybrid flying and contact loco-manipulation (workshop version)
Josep Marti-Saumell, Joan Sola, Angel Santamaria-Navarro +1
This paper introduces Borinot, an open-source flying robotic platform designed to perform hybrid agile locomotion and manipulation. This platform features a compact and powerful he…
ACHORD: Communication-Aware Multi-Robot Coordination with Intermittent Connectivity
Maira Saboia, Lillian Clark, Vivek Thangavelu +16
Communication is an important capability for multi-robot exploration because (1) inter-robot communication (comms) improves coverage efficiency and (2) robot-to-base comms improves…
Full-Body Torque-Level Non-linear Model Predictive Control for Aerial Manipulation
Josep Martí-Saumell, Joan Solà, Angel Santamaria-Navarro +1
Non-linear model predictive control (nMPC) is a powerful approach to control complex robots (such as humanoids, quadrupeds, or unmanned aerial manipulators (UAMs)) as it brings imp…
Towards Robust State Estimation by Boosting the Maximum Correntropy Criterion Kalman Filter with Adaptive Behaviors
Seyed Fakoorian, Angel Santamaria-Navarro, Brett T. Lopez +2
This work proposes a resilient and adaptive state estimation framework for robots operating in perceptually-degraded environments. The approach, called Adaptive Maximum Correntropy…