2 citations · 3 across the 7 of their papers we have counts for
7 papers
FlowMaps: Modeling Long-Term Multimodal Object Dynamics with Flow Matching
Francesco Argenziano, Miguel Saavedra-Ruiz, Sacha Morin +3
Joint spatial and temporal understanding of 3D scenes is a crucial requirement for robots deployed in everyday household environments. Such agents must not only comprehend and navi…
Predictive Spatio-Temporal Scene Graphs for Semi-Static Scenes
Miguel Saavedra-Ruiz, Charlie Gauthier, Kumaraditya Gupta +4
We have seen tremendous recent progress in our ability to build "spatio-semantic" representations that enable robots to perform complex reasoning across geometry and semantics. How…
Dynamic Objects Relocalization in Changing Environments with Flow Matching
Francesco Argenziano, Miguel Saavedra-Ruiz, Sacha Morin +2
Task and motion planning are long-standing challenges in robotics, especially when robots have to deal with dynamic environments exhibiting long-term dynamics, such as households o…
Perpetua: Multi-Hypothesis Persistence Modeling for Semi-Static Environments
Miguel Saavedra-Ruiz, Samer B. Nashed, Charlie Gauthier +1
Many robotic systems require extended deployments in complex, dynamic environments. In such deployments, parts of the environment may change between subsequent robot observations.…
The Harmonic Exponential Filter for Nonparametric Estimation on Motion Groups
Miguel Saavedra-Ruiz, Steven A. Parkison, Ria Arora +2
Bayesian estimation is a vital tool in robotics as it allows systems to update the robot state belief using incomplete information from noisy sensors. To render the state estimatio…
One-4-All: Neural Potential Fields for Embodied Navigation
Sacha Morin, Miguel Saavedra-Ruiz, Liam Paull
A fundamental task in robotics is to navigate between two locations. In particular, real-world navigation can require long-horizon planning using high-dimensional RGB images, which…
Monocular Robot Navigation with Self-Supervised Pretrained Vision Transformers
Miguel Saavedra-Ruiz, Sacha Morin, Liam Paull
In this work, we consider the problem of learning a perception model for monocular robot navigation using few annotated images. Using a Vision Transformer (ViT) pretrained with a l…