33 citations · 59 across the 10 of their papers we have counts for
10 papers
Resource-Aware Collaborative Monte Carlo Localization with Distribution Compression
Nicky Zimmerman, Alessandro Giusti, Jérôme Guzzi
Global localization is essential in enabling robot autonomy, and collaborative localization is key for multi-robot systems. In this paper, we address the task of collaborative glob…
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…
Flexible and Fully Quantized Ultra-Lightweight TinyissimoYOLO for Ultra-Low-Power Edge Systems
Julian Moosmann, Hanna Mueller, Nicky Zimmerman +3
This paper deploys and explores variants of TinyissimoYOLO, a highly flexible and fully quantized ultra-lightweight object detection network designed for edge systems with a power…
Constructing Metric-Semantic Maps using Floor Plan Priors for Long-Term Indoor Localization
Nicky Zimmerman, Matteo Sodano, Elias Marks +2
Object-based maps are relevant for scene understanding since they integrate geometric and semantic information of the environment, allowing autonomous robots to robustly localize a…
Fully On-board Low-Power Localization with Multizone Time-of-Flight Sensors on Nano-UAVs
Hanna Müller, Nicky Zimmerman, Tommaso Polonelli +4
Nano-size unmanned aerial vehicles (UAVs) hold enormous potential to perform autonomous operations in complex environments, such as inspection, monitoring or data collection. Moreo…
Long-Term Localization using Semantic Cues in Floor Plan Maps
Nicky Zimmerman, Tiziano Guadagnino, Xieyuanli Chen +2
Lifelong localization in a given map is an essential capability for autonomous service robots. In this paper, we consider the task of long-term localization in a changing indoor en…
IR-MCL: Implicit Representation-Based Online Global Localization
Haofei Kuang, Xieyuanli Chen, Tiziano Guadagnino +3
Determining the state of a mobile robot is an essential building block of robot navigation systems. In this paper, we address the problem of estimating the robots pose in an indoor…
Robust Onboard Localization in Changing Environments Exploiting Text Spotting
Nicky Zimmerman, Louis Wiesmann, Tiziano Guadagnino +3
Robust localization in a given map is a crucial component of most autonomous robots. In this paper, we address the problem of localizing in an indoor environment that changes and w…
Training Lightweight CNNs for Human-Nanodrone Proximity Interaction from Small Datasets using Background Randomization
Marco Ferri, Dario Mantegazza, Elia Cereda +5
We consider the task of visually estimating the pose of a human from images acquired by a nearby nano-drone; in this context, we propose a data augmentation approach based on synth…
Fully Onboard AI-powered Human-Drone Pose Estimation on Ultra-low Power Autonomous Flying Nano-UAVs
Daniele Palossi, Nicky Zimmerman, Alessio Burrello +6
Artificial intelligence-powered pocket-sized air robots have the potential to revolutionize the Internet-of-Things ecosystem, acting as autonomous, unobtrusive, and ubiquitous smar…