29 citations · 81 across the 21 of their papers we have counts for
8 papers · 1 filter
LocalNav: Distilling Frontier VLMs and Embodied RL for On-Device Object Goal Navigation
Nicolas Baumann, Liam Boyle, Pu Deng +5
Vision Language Models (VLMs) have emerged in the robotic domain as a powerful tool that enables environmental perception with language context, serving as a catalyst for open-voca…
RobotxR1: Enabling Embodied Robotic Intelligence on Large Language Models through Closed-Loop Reinforcement Learning
Liam Boyle, Nicolas Baumann, Paviththiren Sivasothilingam +2
Future robotic systems operating in real-world environments will require on-board embodied intelligence without continuous cloud connection, balancing capabilities with constraints…
BatDeck -- Ultra Low-power Ultrasonic Ego-velocity Estimation and Obstacle Avoidance on Nano-drones
Hanna Müller, Victor Kartsch, Michele Magno +1
Nano-drones, with their small, lightweight design, are ideal for confined-space rescue missions and inherently safe for human interaction. However, their limited payload restricts…
Ultra-Lightweight Collaborative Mapping for Robot Swarms
Vlad Niculescu, Tommaso Polonelli, Michele Magno +1
A key requirement in robotics is the ability to simultaneously self-localize and map a previously unknown environment, relying primarily on onboard sensing and computation. Achievi…
BatDeck: Advancing Nano-drone Navigation with Low-power Ultrasound-based Obstacle Avoidance
Hanna Müller, Victor Kartsch, Michele Magno +1
Nano-drones, distinguished by their agility, minimal weight, and cost-effectiveness, are particularly well-suited for exploration in confined, cluttered and narrow spaces. Recogniz…
Fully Onboard Low-Power Localization with Semantic Sensor Fusion on a Nano-UAV using Floor Plans
Nicky Zimmerman, Hanna Müller, Michele Magno +1
Nano-sized unmanned aerial vehicles (UAVs) are well-fit for indoor applications and for close proximity to humans. To enable autonomy, the nano-UAV must be able to self-localize in…
NanoSLAM: Enabling Fully Onboard SLAM for Tiny Robots
Vlad Niculescu, Tommaso Polonelli, Michele Magno +1
Perceiving and mapping the surroundings are essential for enabling autonomous navigation in any robotic platform. The algorithm class that enables accurate mapping while correcting…
Fully Onboard SLAM for Distributed Mapping with a Swarm of Nano-Drones
Carl Friess, Vlad Niculescu, Tommaso Polonelli +2
The use of Unmanned Aerial Vehicles (UAVs) is rapidly increasing in applications ranging from surveillance and first-aid missions to industrial automation involving cooperation wit…