59 citations · 391 across the 32 of their papers we have counts for
33 papers
Barrier Certificate Synthesis for Non-Polynomial Robotic Dynamics via Polynomial Lifting
Shivam Chaubey, Francesco Verdoja, Shankar Deka +1
Safe operation of robotic systems requires trajectories to remain within a prescribed safe set under admissible control inputs. Barrier certificates provide such guarantees by cert…
An Information-Space Perspective to Scene Graph Sufficiency for Robotic Task Planning
Başak Sakçak, Francesco Verdoja
Planning in complex environments requires task specifications grounded in representations that capture objects, relations, and affordances; scene graphs meet this need, but their s…
ReGIL: Retrieval-Guided Imitation Learning from a Single Demonstration
Yuying Zhang, Francesco Verdoja, Wenyan Yang +1
Learning robot manipulation policies with deep neural networks from a single demonstration remains highly challenging, as even small deviations from the demonstrated trajectory can…
Rheos: Modelling Continuous Motion Dynamics in Hierarchical 3D Scene Graphs
Iacopo Catalano, Francesco Verdoja, Javier Civera +2
3D Scene Graphs (3DSGs) provide hierarchical, multi-resolution abstractions that encode the geometric and semantic structure of an environment, yet their treatment of dynamics rema…
Relational Scene Graphs for Object Grounding of Natural Language Commands
Julia Kuhn, Francesco Verdoja, Tsvetomila Mihaylova +1
Robots are finding wider adoption in human environments, increasing the need for natural human-robot interaction. However, understanding a natural language command requires the rob…
Event-Grounding Graph: Unified Spatio-Temporal Scene Graph from Robotic Observations
Phuoc Nguyen, Francesco Verdoja, Ville Kyrki
A fundamental aspect for building intelligent autonomous robots that can assist humans in their daily lives is the construction of rich environmental representations. While advance…
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,…
MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects
Yuying Zhang, Kevin Sebastian Luck, Francesco Verdoja +2
Mobile manipulation is a critical capability for robots operating in diverse, real-world environments. However, manipulating deformable objects and materials remains a major challe…
Minimal Intervention Shared Control with Guaranteed Safety under Non-Convex Constraints
Shivam Chaubey, Francesco Verdoja, Shankar Deka +1
Shared control combines human intention with autonomous decision-making. At the low level, the primary goal is to maintain safety regardless of the user's input to the system. Howe…
REACT: Real-time Efficient Attribute Clustering and Transfer for Updatable 3D Scene Graph
Phuoc Nguyen, Francesco Verdoja, Ville Kyrki
Modern-day autonomous robots need high-level map representations to perform sophisticated tasks. Recently, 3D scene graphs (3DSGs) have emerged as a promising alternative to tradit…
ReMoBot: Retrieval-Based Few-Shot Imitation Learning for Mobile Manipulation with Vision Foundation Models
Yuying Zhang, Wenyan Yang, Francesco Verdoja +2
Imitation learning (IL) algorithms typically distill demonstrations into parametric policies to mimic expert behavior. However, with limited data and partial observability, such as…
Jointly Learning Cost and Constraints from Demonstrations for Safe Trajectory Generation
Shivam Chaubey, Francesco Verdoja, Ville Kyrki
Learning from Demonstration allows robots to mimic human actions. However, these methods do not model constraints crucial to ensure safety of the learned skill. Moreover, even when…
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…
Constrained Generative Sampling of 6-DoF Grasps
Jens Lundell, Francesco Verdoja, Tran Nguyen Le +3
Most state-of-the-art data-driven grasp sampling methods propose stable and collision-free grasps uniformly on the target object. For bin-picking, executing any of those reachable…
LSVL: Large-scale season-invariant visual localization for UAVs
Jouko Kinnari, Riccardo Renzulli, Francesco Verdoja +1
Localization of autonomous unmanned aerial vehicles (UAVs) relies heavily on Global Navigation Satellite Systems (GNSS), which are susceptible to interference. Especially in securi…
Bayesian Floor Field: Transferring people flow predictions across environments
Francesco Verdoja, Tomasz Piotr Kucner, Ville Kyrki
Mapping people dynamics is a crucial skill for robots, because it enables them to coexist in human-inhabited environments. However, learning a model of people dynamics is a time co…
Season-invariant GNSS-denied visual localization for UAVs
Jouko Kinnari, Francesco Verdoja, Ville Kyrki
Localization without Global Navigation Satellite Systems (GNSS) is a critical functionality in autonomous operations of unmanned aerial vehicles (UAVs). Vision-based localization o…
GNSS-denied geolocalization of UAVs by visual matching of onboard camera images with orthophotos
Jouko Kinnari, Francesco Verdoja, Ville Kyrki
Localization of low-cost Unmanned Aerial Vehicles (UAVs) often relies on Global Navigation Satellite Systems (GNSS). GNSS are susceptible to both natural disruptions to radio signa…
Augmented Environment Representations with Complete Object Models
Krishnananda Prabhu Sivananda, Francesco Verdoja, Ville Kyrki
While 2D occupancy maps commonly used in mobile robotics enable safe navigation in indoor environments, in order for robots to understand and interact with their environment and it…
DDGC: Generative Deep Dexterous Grasping in Clutter
Jens Lundell, Francesco Verdoja, Ville Kyrki
Recent advances in multi-fingered robotic grasping have enabled fast 6-Degrees-Of-Freedom (DOF) single object grasping. Multi-finger grasping in cluttered scenes, on the other hand…
Multi-FinGAN: Generative Coarse-To-Fine Sampling of Multi-Finger Grasps
Jens Lundell, Enric Corona, Tran Nguyen Le +5
While there exists many methods for manipulating rigid objects with parallel-jaw grippers, grasping with multi-finger robotic hands remains a quite unexplored research topic. Reaso…
Online Object-Oriented Semantic Mapping and Map Updating
Nils Dengler, Tobias Zaenker, Francesco Verdoja +1
Creating and maintaining an accurate representation of the environment is an essential capability for every service robot. Especially for household robots acting in indoor environm…