173 citations · 876 across the 56 of their papers we have counts for
6 papers · 1 filter
A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations
Sohan Rudra, Saksham Goel, Anirban Santara +6
Object-goal navigation (Object-nav) entails searching, recognizing and navigating to a target object. Object-nav has been extensively studied by the Embodied-AI community, but most…
Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization
Thomas Lew, Sumeet Singh, Mario Prats +11
We propose a framework to enable multipurpose assistive mobile robots to autonomously wipe tables to clean spills and crumbs. This problem is challenging, as it requires planning w…
Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation
Xuesu Xiao, Tingnan Zhang, Krzysztof Choromanski +14
Despite decades of research, existing navigation systems still face real-world challenges when deployed in the wild, e.g., in cluttered home environments or in human-occupied publi…
Implicit Two-Tower Policies
Yunfan Zhao, Qingkai Pan, Krzysztof Choromanski +2
We present a new class of structured reinforcement learning policy-architectures, Implicit Two-Tower (ITT) policies, where the actions are chosen based on the attention scores of t…
Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language
Andy Zeng, Maria Attarian, Brian Ichter +10
Large pretrained (e.g., "foundation") models exhibit distinct capabilities depending on the domain of data they are trained on. While these domains are generic, they may only barel…
Multiscale Sensor Fusion and Continuous Control with Neural CDEs
Sumeet Singh, Francis McCann Ramirez, Jacob Varley +2
Though robot learning is often formulated in terms of discrete-time Markov decision processes (MDPs), physical robots require near-continuous multiscale feedback control. Machines…