6 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…
PerceptTwin: Semantic Scene Reconstruction for Iterative LLM Planning and Verification
Charlie Gauthier, Sacha Morin, Liam Paull
Simulation environments are useful for both robot policy learning and planning verification and validation. Traditionally, the process of creating a simulation was onerous. Creatin…
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…
Agentic Scene Policies
Sacha Morin, Kumaraditya Gupta, Mahtab Sandhu +4
Designing or learning robot policies that generalize zero-shot across a range of language instructions and objects is a core problem in robotics. Vision-Language-Action models (VLA…
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.…
Safety Representations for Safer Policy Learning
Kaustubh Mani, Vincent Mai, Charlie Gauthier +3
Reinforcement learning algorithms typically necessitate extensive exploration of the state space to find optimal policies. However, in safety-critical applications, the risks assoc…