3 papers
cs.RO2025
QuASH: Using Natural-Language Heuristics to Query Visual-Language Robotic Maps
Matti Pekkanen, Francesco Verdoja, Ville Kyrki
Embeddings from Visual-Language Models are increasingly utilized to represent semantics in robotic maps, offering an open-vocabulary scene understanding that surpasses traditional,…
cs.RO2024
Do Visual-Language Grid Maps Capture Latent Semantics?
Matti Pekkanen, Tsvetomila Mihaylova, Francesco Verdoja +1
Visual-language models (VLMs) have recently been introduced in robotic mapping using the latent representations, i.e., embeddings, of the VLMs to represent semantics in the map. Th…
cs.RO2023
Object-Oriented Grid Mapping in Dynamic Environments
Matti Pekkanen, Francesco Verdoja, Ville Kyrki
Grid maps, especially occupancy grid maps, are ubiquitous in many mobile robot applications. To simplify the process of learning the map, grid maps subdivide the world into a grid…