107 citations · 390 across the 26 of their papers we have counts for
6 papers · 1 filter
Language-guided Semantic Mapping and Mobile Manipulation in Partially Observable Environments
Siddharth Patki, Ethan Fahnestock, Thomas M. Howard +1
Recent advances in data-driven models for grounded language understanding have enabled robots to interpret increasingly complex instructions. Two fundamental limitations of these m…
DIODE: A Dense Indoor and Outdoor DEpth Dataset
Igor Vasiljevic, Nick Kolkin, Shanyi Zhang +8
We introduce DIODE, a dataset that contains thousands of diverse high resolution color images with accurate, dense, long-range depth measurements. DIODE (Dense Indoor/Outdoor DEpth…
Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards
Falcon Z. Dai, Matthew R. Walter
We propose a new complexity measure for Markov decision processes (MDPs), the maximum expected hitting cost (MEHC). This measure tightens the closely related notion of diameter [JO…
Multigrid Neural Memory
Tri Huynh, Michael Maire, Matthew R. Walter
We introduce a novel approach to endowing neural networks with emergent, long-term, large-scale memory. Distinct from strategies that connect neural networks to external memory ban…
Inferring Compact Representations for Efficient Natural Language Understanding of Robot Instructions
Siddharth Patki, Andrea F. Daniele, Matthew R. Walter +1
The speed and accuracy with which robots are able to interpret natural language is fundamental to realizing effective human-robot interaction. A great deal of attention has been pa…
The AI Driving Olympics at NeurIPS 2018
Julian Zilly, Jacopo Tani, Breandan Considine +14
Despite recent breakthroughs, the ability of deep learning and reinforcement learning to outperform traditional approaches to control physically embodied robotic agents remains lar…