2 citations · 2 across the 8 of their papers we have counts for
12 papers
Joint Task Assistance Planning via Nested Branch and Bound (Extended Version)
Omer Daube, Oren Salzman
We introduce and study the Joint Task Assistance Planning problem which generalizes prior work on optimizing assistance in robotic collaboration. In this setting, two robots operat…
Diverse Transformer Decoding for Offline Reinforcement Learning Using Financial Algorithmic Approaches
Dan Elbaz, Oren Salzman
Offline Reinforcement Learning (RL) algorithms learn a policy using a fixed training dataset, which is then deployed online to interact with the environment and make decisions. Tra…
Offline Task Assistance Planning on a Graph:Theoretic and Algorithmic Foundations
Eitan Bloch, Oren Salzman
In this work we introduce the problem of task assistance planning where we are given two robots Rtask and Rassist. The first robot, Rtask, is in charge of performing a given task b…
Wall Street Tree Search: Risk-Aware Planning for Offline Reinforcement Learning
Dan Elbaz, Gal Novik, Oren Salzman
Offline reinforcement-learning (RL) algorithms learn to make decisions using a given, fixed training dataset without online data collection. This problem setting is captivating bec…
Provably Constant-time Planning and Replanning for Real-time Grasping Objects off a Conveyor Belt
Fahad Islam, Oren Salzman, Aditya Agarwal +1
In warehouse and manufacturing environments, manipulation platforms are frequently deployed at conveyor belts to perform pick and place tasks. Because objects on the conveyor belts…
Provably Constant-time Planning and Replanning for Real-time Grasping Objects off a Conveyor Belt
Fahad Islam, Oren Salzman, Aditya Agarwal +1
In warehouse and manufacturing environments, manipulation platforms are frequently deployed at conveyor belts to perform pick and place tasks. Because objects on the conveyor belts…
Task-Informed Fidelity Management for Speeding Up Robotics Simulation
Abhijeet Tallavajhula, Adrian Schoisengeier, Sung-Kyun Kim +3
Simulators are an important tool in robotics that is used to develop robot software and generate synthetic data for machine learning algorithms. Faster simulation can result in bet…
Planning, Learning and Reasoning Framework for Robot Truck Unloading
Fahad Islam, Anirudh Vemula, Sung-Kyun Kim +3
We consider the task of autonomously unloading boxes from trucks using an industrial manipulator robot. There are multiple challenges that arise: (1) real-time motion planning for…
A Planning Framework for Persistent, Multi-UAV Coverage with Global Deconfliction
Tushar Kusnur, Shohin Mukherjee, Dhruv Mauria Saxena +4
Planning for multi-robot coverage seeks to determine collision-free paths for a fleet of robots, enabling them to collectively observe points of interest in an environment. Persist…
Provable Indefinite-Horizon Real-Time Planning for Repetitive Tasks
Fahad Islam, Oren Salzman, Maxim Likhachev
In many robotic manipulation scenarios, robots often have to perform highly-repetitive tasks in structured environments e.g. sorting mail in a mailroom or pick and place objects on…
Effective Footstep Planning Using Homotopy-Class Guidance
Vinitha Ranganeni, Sahit Chintalapudi, Oren Salzman +1
Planning the motion for humanoid robots is a computationally-complex task due to the high dimensionality of the system. Thus, a common approach is to first plan in the low-dimensio…
Online, interactive user guidance for high-dimensional, constrained motion planning
Fahad Islam, Oren Salzman, Maxim Likhachev
We consider the problem of planning a collision-free path for a high-dimensional robot. Specifically, we suggest a planning framework where a motion-planning algorithm can obtain g…