no code implementations • 26 Apr 2024 • Martina Stadler Kurtz, Samuel Prentice, Yasmin Veys, Long Quang, Carlos Nieto-Granda, Michael Novitzky, Ethan Stump, Nicholas Roy
In this paper, we describe the deployment of a planning system that used a hierarchy of planners to execute collaborative multiagent navigation tasks in real-world, unknown environments.
no code implementations • 9 Apr 2024 • Kunal Garg, Jacob Arkin, Songyuan Zhang, Nicholas Roy, Chuchu Fan
Multi-agent robotic systems are prone to deadlocks in an obstacle environment where the system can get stuck away from its desired location under a smooth low-level control policy.
1 code implementation • 13 Feb 2024 • Yongchao Chen, Jacob Arkin, Yilun Hao, Yang Zhang, Nicholas Roy, Chuchu Fan
Prompt optimization aims to find the best prompt to a large language model (LLM) for a given task.
no code implementations • 23 Dec 2023 • Moritz Harmel, Anubhav Paras, Andreas Pasternak, Nicholas Roy, Gary Linscott
However, running reinforcement learning experiments on the required scale for autonomous driving is extremely difficult.
no code implementations • 10 Nov 2023 • Xiaoyi Cai, Siddharth Ancha, Lakshay Sharma, Philip R. Osteen, Bernadette Bucher, Stephen Phillips, Jiuguang Wang, Michael Everett, Nicholas Roy, Jonathan P. How
For uncertainty quantification, we efficiently model both aleatoric and epistemic uncertainty by learning discrete traction distributions and probability densities of the traction predictor's latent features.
3 code implementations • 10 Jun 2023 • Yongchao Chen, Jacob Arkin, Charles Dawson, Yang Zhang, Nicholas Roy, Chuchu Fan
Rather than using LLMs to directly plan task sub-goals, we instead perform few-shot translation from natural language task descriptions to an intermediate task representation that can then be consumed by a TAMP algorithm to jointly solve the task and motion plan.
no code implementations • 26 May 2023 • Emily Liu, Michael Noseworthy, Nicholas Roy
In this paper, we investigate a scenario in which a robot learns a low-dimensional representation of a door given a video of the door opening or closing.
no code implementations • 28 Oct 2021 • Nicholas Roy, Ingmar Posner, Tim Barfoot, Philippe Beaudoin, Yoshua Bengio, Jeannette Bohg, Oliver Brock, Isabelle Depatie, Dieter Fox, Dan Koditschek, Tomas Lozano-Perez, Vikash Mansinghka, Christopher Pal, Blake Richards, Dorsa Sadigh, Stefan Schaal, Gaurav Sukhatme, Denis Therien, Marc Toussaint, Michiel Van de Panne
Machine learning has long since become a keystone technology, accelerating science and applications in a broad range of domains.
no code implementations • 1 Jul 2021 • Michael Noseworthy, Caris Moses, Isaiah Brand, Sebastian Castro, Leslie Kaelbling, Tomás Lozano-Pérez, Nicholas Roy
Long horizon sequential manipulation tasks are effectively addressed hierarchically: at a high level of abstraction the planner searches over abstract action sequences, and when a plan is found, lower level motion plans are generated.
no code implementations • 21 May 2021 • Matthew R. Walter, Siddharth Patki, Andrea F. Daniele, Ethan Fahnestock, Felix Duvallet, Sachithra Hemachandra, Jean Oh, Anthony Stentz, Nicholas Roy, Thomas M. Howard
This progress now creates an opportunity for robots to operate not only in isolation, but also with and alongside humans in our complex environments.
no code implementations • 6 Nov 2020 • Yorai Shaoul, Katherine Liu, Kyel Ok, Nicholas Roy
We show that self-labelling challenging triplets--choosing positive examples separated by large temporal distances and negative examples close in the descriptor space--improves the quality of the learned descriptors for the multi-object tracking task.
no code implementations • 6 Jun 2020 • Caris Moses, Michael Noseworthy, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Nicholas Roy
Given a novel object, the objective is to maximize reward with few interactions.
1 code implementation • 1 Jun 2020 • Valentin Peretroukhin, Matthew Giamou, David M. Rosen, W. Nicholas Greene, Nicholas Roy, Jonathan Kelly
Accurate rotation estimation is at the heart of robot perception tasks such as visual odometry and object pose estimation.
no code implementations • CONLL 2019 • Subhro Roy, Michael Noseworthy, Rohan Paul, Daehyung Park, Nicholas Roy
We therefore reframe the grounding problem from the perspective of coreference detection and propose a neural network that detects when two expressions are referring to the same object.
no code implementations • 3 Jun 2018 • William Vega-Brown, Nicholas Roy
We define an admissibility condition for abstractions expressed using angelic semantics and show that these conditions allow us to accelerate planning while preserving the ability to find the optimal motion plan.
no code implementations • 30 Nov 2017 • Genevieve Flaspohler, Nicholas Roy, Yogesh Girdhar
The gap between our ability to collect interesting data and our ability to analyze these data is growing at an unprecedented rate.
no code implementations • 29 Nov 2017 • Thomas Kollar, Stefanie Tellex, Matthew Walter, Albert Huang, Abraham Bachrach, Sachi Hemachandra, Emma Brunskill, Ashis Banerjee, Deb Roy, Seth Teller, Nicholas Roy
Symbolic models capture linguistic structure but have not scaled successfully to handle the diverse language produced by untrained users.
no code implementations • ICCV 2017 • W. Nicholas Greene, Nicholas Roy
We propose a lightweight method for dense online monocular depth estimation capable of reconstructing 3D meshes on computationally constrained platforms.
no code implementations • 1 Aug 2017 • Valentin Peretroukhin, William Vega-Brown, Nicholas Roy, Jonathan Kelly
Many algorithms in computer vision and robotics make strong assumptions about uncertainty, and rely on the validity of these assumptions to produce accurate and consistent state estimates.
no code implementations • 12 May 2014 • Joshua Joseph, Javier Velez, Nicholas Roy
Batch Reinforcement Learning (RL) algorithms attempt to choose a policy from a designer-provided class of policies given a fixed set of training data.
no code implementations • 18 Jan 2014 • Javier Velez, Garrett Hemann, Albert S. Huang, Ingmar Posner, Nicholas Roy
In particular, the performance of detection algorithms is commonly sensitive to the position of the sensor relative to the objects in the scene.
no code implementations • 16 Jan 2014 • Ruijie He, Emma Brunskill, Nicholas Roy
We also demonstrate our algorithm being used to control a real robotic helicopter in a target monitoring experiment, which suggests that our approach has practical potential for planning in real-world, large partially observable domains where a multi-step lookahead is required to achieve good performance.
no code implementations • 26 Sep 2013 • Alborz Geramifard, Thomas J. Walsh, Nicholas Roy, Jonathan How
Matching pursuit (MP) methods are a promising class of feature construction algorithms for value function approximation.
no code implementations • NeurIPS 2010 • Finale Doshi-Velez, David Wingate, Nicholas Roy, Joshua B. Tenenbaum
We consider reinforcement learning in partially observable domains where the agent can query an expert for demonstrations.