6 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…
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…
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…
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…