4 papers
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,…
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…
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…
Localization Under Consistent Assumptions Over Dynamics
Matti Pekkanen, Francesco Verdoja, Ville Kyrki
Accurate maps are a prerequisite for virtually all mobile robot tasks. Most state-of-the-art maps assume a static world; therefore, dynamic objects are filtered out of the measurem…