13 citations · 14 across the 8 of their papers we have counts for
8 papers
Runtime Monitoring of Perception-Based Autonomous Systems via Embedding Temporal Logic
Parv Kapoor, Abigail Hammer, Ashish Kapoor +2
Runtime monitoring of autonomous systems traditionally relies on mapping continuous sensor observations to discrete logical propositions defined over low-dimensional state variable…
DreamControl-v2: Simpler and Scalable Autonomous Humanoid Skills via Trainable Guided Diffusion Priors
Sudarshan Harithas, Sangkyung Kwak, Pushkal Katara +6
Developing robust autonomous loco-manipulation skills for humanoids remains an open problem in robotics. While RL has been applied successfully to legged locomotion, applying it to…
DreamControl: Human-Inspired Whole-Body Humanoid Control for Scene Interaction via Guided Diffusion
Dvij Kalaria, Sudarshan S Harithas, Pushkal Katara +7
We introduce DreamControl, a novel methodology for learning autonomous whole-body humanoid skills. DreamControl leverages the strengths of diffusion models and Reinforcement Learni…
MatMamba: A Matryoshka State Space Model
Abhinav Shukla, Sai Vemprala, Aditya Kusupati +1
State Space Models (SSMs) like Mamba2 are a promising alternative to Transformers, with faster theoretical training and inference times -- especially for long context lengths. Rece…
Logically Constrained Robotics Transformers for Enhanced Perception-Action Planning
Parv Kapoor, Sai Vemprala, Ashish Kapoor
With the advent of large foundation model based planning, there is a dire need to ensure their output aligns with the stakeholder's intent. When these models are deployed in the re…
Foundation Models in Robotics: Applications, Challenges, and the Future
Roya Firoozi, Johnathan Tucker, Stephen Tian +12
We survey applications of pretrained foundation models in robotics. Traditional deep learning models in robotics are trained on small datasets tailored for specific tasks, which li…
GRID: A Platform for General Robot Intelligence Development
Sai Vemprala, Shuhang Chen, Abhinav Shukla +2
Developing machine intelligence abilities in robots and autonomous systems is an expensive and time consuming process. Existing solutions are tailored to specific applications and…
EvDNeRF: Reconstructing Event Data with Dynamic Neural Radiance Fields
Anish Bhattacharya, Ratnesh Madaan, Fernando Cladera +7
We present EvDNeRF, a pipeline for generating event data and training an event-based dynamic NeRF, for the purpose of faithfully reconstructing eventstreams on scenes with rigid an…