no code implementations • 15 May 2025 • Milan Ganai, Rohan Sinha, Christopher Agia, Daniel Morton, Marco Pavone
FORTRESS outperforms on-the-fly prompting of slow reasoning models in safety classification accuracy on synthetic benchmarks and real-world ANYmal robot data, and further improves system safety and planning success in simulation and on quadrotor hardware for urban navigation.
no code implementations • 11 Jul 2024 • Rohan Sinha, Amine Elhafsi, Christopher Agia, Matthew Foutter, Edward Schmerling, Marco Pavone
Foundation models, e. g., large language models (LLMs), trained on internet-scale data possess zero-shot generalization capabilities that make them a promising technology towards detecting and mitigating out-of-distribution failure modes of robotic systems.
1 code implementation • 21 Oct 2022 • Christopher Agia, Toki Migimatsu, Jiajun Wu, Jeannette Bohg
We further demonstrate how STAP can be used for task and motion planning by estimating the geometric feasibility of skill sequences provided by a task planner.
1 code implementation • 11 Jul 2022 • Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir, Ondrej Miksik, Vibhav Vineet, Mustafa Mukadam, Liam Paull, Florian Shkurti
3D scene graphs (3DSGs) are an emerging description; unifying symbolic, topological, and metric scene representations.
no code implementations • 16 Dec 2020 • Ran Cheng, Christopher Agia, Yuan Ren, Xinhai Li, Liu Bingbing
With the increasing reliance of self-driving and similar robotic systems on robust 3D vision, the processing of LiDAR scans with deep convolutional neural networks has become a trend in academia and industry alike.
Ranked #3 on
3D Semantic Scene Completion
on SemanticKITTI