1.2k citations · 3.1k across the 91 of their papers we have counts for
10 papers · 1 filter
Sample-Efficient Learning of Nonprehensile Manipulation Policies via Physics-Based Informed State Distributions
Lerrel Pinto, Aditya Mandalika, Brian Hou +1
This paper proposes a sample-efficient yet simple approach to learning closed-loop policies for nonprehensile manipulation. Although reinforcement learning (RL) can learn closed-lo…
Bayes-CPACE: PAC Optimal Exploration in Continuous Space Bayes-Adaptive Markov Decision Processes
Gilwoo Lee, Sanjiban Choudhury, Brian Hou +1
We present the first PAC optimal algorithm for Bayes-Adaptive Markov Decision Processes (BAMDPs) in continuous state and action spaces, to the best of our knowledge. The BAMDP fram…
Bayesian Policy Optimization for Model Uncertainty
Gilwoo Lee, Brian Hou, Aditya Mandalika +3
Addressing uncertainty is critical for autonomous systems to robustly adapt to the real world. We formulate the problem of model uncertainty as a continuous Bayes-Adaptive Markov D…
Improved Proximity, Contact, and Force Sensing via Optimization of Elastomer-Air Interface Geometry
Patrick E. Lancaster, Joshua R. Smith, Siddhartha S. Srinivasa
We describe a single fingertip-mounted sensing system for robot manipulation that provides proximity (pre-touch), contact detection (touch), and force sensing (post-touch). The sen…
HARMONIC: A Multimodal Dataset of Assistive Human-Robot Collaboration
Benjamin A. Newman, Reuben M. Aronson, Siddartha S. Srinivasa +2
We present the Human And Robot Multimodal Observations of Natural Interactive Collaboration (HARMONIC) data set. This is a large multimodal data set of human interactions with a ro…
Balancing Shared Autonomy with Human-Robot Communication
Rosario Scalise, Yonatan Bisk, Maxwell Forbes +3
Robotic agents that share autonomy with a human should leverage human domain knowledge and account for their preferences when completing a task. This extra knowledge can dramatical…
Towards Robotic Feeding: Role of Haptics in Fork-based Food Manipulation
Tapomayukh Bhattacharjee, Gilwoo Lee, Hanjun Song +1
Autonomous feeding is challenging because it requires manipulation of food items with various compliance, sizes, and shapes. To understand how humans manipulate food items during f…
Lazy Receding Horizon A* for Efficient Path Planning in Graphs with Expensive-to-Evaluate Edges
Aditya Mandalika, Oren Salzman, Siddhartha Srinivasa
Motion-planning problems, such as manipulation in cluttered environments, often require a collision-free shortest path to be computed quickly given a roadmap graph. Typically, the…
Recurrent Predictive State Policy Networks
Ahmed Hefny, Zita Marinho, Wen Sun +2
We introduce Recurrent Predictive State Policy (RPSP) networks, a recurrent architecture that brings insights from predictive state representations to reinforcement learning in par…
Trust-Aware Decision Making for Human-Robot Collaboration: Model Learning and Planning
Min Chen, Stefanos Nikolaidis, Harold Soh +2
Trust in autonomy is essential for effective human-robot collaboration and user adoption of autonomous systems such as robot assistants. This paper introduces a computational model…