90 citations · 117 across the 12 of their papers we have counts for
7 papers · 1 filter
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…
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…
ConBaT: Control Barrier Transformer for Safe Policy Learning
Yue Meng, Sai Vemprala, Rogerio Bonatti +2
Large-scale self-supervised models have recently revolutionized our ability to perform a variety of tasks within the vision and language domains. However, using such models for aut…
Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functions
Wenhao Luo, Wen Sun, Ashish Kapoor
Reinforcement Learning (RL) and continuous nonlinear control have been successfully deployed in multiple domains of complicated sequential decision-making tasks. However, given the…
Learning to Gather Information via Imitation
Sanjiban Choudhury, Ashish Kapoor, Gireeja Ranade +1
The budgeted information gathering problem - where a robot with a fixed fuel budget is required to maximize the amount of information gathered from the world - appears in practice…
Probabilistic Safety Programs
Ashish Kapoor, Debadeepta Dey, Shital Shah
Achieving safe control under uncertainty is a key problem that needs to be tackled for enabling real-world autonomous robots and cyber-physical systems. This paper introduces Proba…