Search Results for author: Gregory Dudek

Found 36 papers, 7 papers with code

Anomaly Detection for Scalable Task Grouping in Reinforcement Learning-based RAN Optimization

no code implementations6 Dec 2023 Jimmy Li, Igor Kozlov, Di wu, Xue Liu, Gregory Dudek

This coincides with a rapid increase in the number of cell sites worldwide, driven largely by dramatic growth in cellular network traffic.

Anomaly Detection

Working Backwards: Learning to Place by Picking

no code implementations4 Dec 2023 Oliver Limoyo, Abhisek Konar, Trevor Ablett, Jonathan Kelly, Francois R. Hogan, Gregory Dudek

With LPP, we approach the learning of robotic object placement policies by reversing the grasping process and exploiting the inherent symmetry of the pick and place problems.

Learning active tactile perception through belief-space control

no code implementations30 Nov 2023 Jean-François Tremblay, David Meger, Francois Hogan, Gregory Dudek

These robots will need to sense these properties through interaction prior to performing downstream tasks with the objects.


Generalizable Imitation Learning Through Pre-Trained Representations

no code implementations15 Nov 2023 Wei-Di Chang, Francois Hogan, David Meger, Gregory Dudek

In this paper we leverage self-supervised vision transformer models and their emergent semantic abilities to improve the generalization abilities of imitation learning policies.

Clustering Imitation Learning

Adaptive Dynamic Programming for Energy-Efficient Base Station Cell Switching

no code implementations5 Oct 2023 Junliang Luo, Yi Tian Xu, Di wu, Michael Jenkin, Xue Liu, Gregory Dudek

In this work, we propose an approximate dynamic programming (ADP)-based method coupled with online optimization to switch on/off the cells of base stations to reduce network power consumption while maintaining adequate Quality of Service (QoS) metrics.

Imitation Learning from Observation through Optimal Transport

no code implementations2 Oct 2023 Wei-Di Chang, Scott Fujimoto, David Meger, Gregory Dudek

Imitation Learning from Observation (ILfO) is a setting in which a learner tries to imitate the behavior of an expert, using only observational data and without the direct guidance of demonstrated actions.

Continuous Control Imitation Learning

CARTIER: Cartographic lAnguage Reasoning Targeted at Instruction Execution for Robots

no code implementations21 Jul 2023 Dmitriy Rivkin, Nikhil Kakodkar, Francois Hogan, Bobak H. Baghi, Gregory Dudek

This work explores the capacity of large language models (LLMs) to address problems at the intersection of spatial planning and natural language interfaces for navigation. Our focus is on following relatively complex instructions that are more akin to natural conversation than traditional explicit procedural directives seen in robotics.


Neural Bee Colony Optimization: A Case Study in Public Transit Network Design

no code implementations18 May 2023 Andrew Holliday, Gregory Dudek

In this work we explore the combination of metaheuristics and learned neural network solvers for combinatorial optimization.

Combinatorial Optimization

Communication Load Balancing via Efficient Inverse Reinforcement Learning

no code implementations22 Mar 2023 Abhisek Konar, Di wu, Yi Tian Xu, Seowoo Jang, Steve Liu, Gregory Dudek

Engineering this reward function is challenging, because it involves the need for expert knowledge and there lacks a general consensus on the form of an optimal reward function.

reinforcement-learning Reinforcement Learning (RL)

Policy Reuse for Communication Load Balancing in Unseen Traffic Scenarios

no code implementations22 Mar 2023 Yi Tian Xu, Jimmy Li, Di wu, Michael Jenkin, Seowoo Jang, Xue Liu, Gregory Dudek

When deploying to an unknown traffic scenario, we select a policy from the policy bank based on the similarity between the previous-day traffic of the current scenario and the traffic observed during training.

Reinforcement Learning (RL)

Multi-agent Attention Actor-Critic Algorithm for Load Balancing in Cellular Networks

no code implementations14 Mar 2023 Jikun Kang, Di wu, Ju Wang, Ekram Hossain, Xue Liu, Gregory Dudek

In cellular networks, User Equipment (UE) handoff from one Base Station (BS) to another, giving rise to the load balancing problem among the BSs.

Self-Supervised Transformer Architecture for Change Detection in Radio Access Networks

no code implementations3 Feb 2023 Igor Kozlov, Dmitriy Rivkin, Wei-Di Chang, Di wu, Xue Liu, Gregory Dudek

Such networks undergo frequent and often heterogeneous changes caused by network operators, who are seeking to tune their system parameters for optimal performance.

Change Detection Self-Supervised Learning

Hypernetworks for Zero-shot Transfer in Reinforcement Learning

no code implementations28 Nov 2022 Sahand Rezaei-Shoshtari, Charlotte Morissette, Francois Robert Hogan, Gregory Dudek, David Meger

In this paper, hypernetworks are trained to generate behaviors across a range of unseen task conditions, via a novel TD-based training objective and data from a set of near-optimal RL solutions for training tasks.

Continuous Control reinforcement-learning +2

Bayesian Q-learning With Imperfect Expert Demonstrations

no code implementations1 Oct 2022 Fengdi Che, Xiru Zhu, Doina Precup, David Meger, Gregory Dudek

Guided exploration with expert demonstrations improves data efficiency for reinforcement learning, but current algorithms often overuse expert information.

Atari Games Q-Learning +2

Trajectory-Constrained Deep Latent Visual Attention for Improved Local Planning in Presence of Heterogeneous Terrain

no code implementations9 Dec 2021 Stefan Wapnick, Travis Manderson, David Meger, Gregory Dudek

We present a reward-predictive, model-based deep learning method featuring trajectory-constrained visual attention for local planning in visual navigation tasks.

Visual Navigation

Average Outward Flux Skeletons for Environment Mapping and Topology Matching

no code implementations27 Nov 2021 Morteza Rezanejad, Babak Samari, Elham Karimi, Ioannis Rekleitis, Gregory Dudek, Kaleem Siddiqi

In topology matching between two given maps and their AOF skeletons, we first find correspondences between points on the AOF skeletons of two different environments.

Loop Closure Detection

MOBA: Multi-teacher Model Based Reinforcement Learning

no code implementations29 Sep 2021 Jikun Kang, Xi Chen, Ju Wang, Chengming Hu, Xue Liu, Gregory Dudek

Results show that, compared with SOTA model-free methods, our method can improve the data efficiency and system performance by up to 75% and 10%, respectively.

Decision Making Knowledge Distillation +4

Multi-batch Reinforcement Learning via Sample Transfer and Imitation Learning

no code implementations29 Sep 2021 Di wu, Tianyu Li, David Meger, Michael Jenkin, Xue Liu, Gregory Dudek

Unfortunately, most online reinforcement learning algorithms require a large number of interactions with the environment to learn a reliable control policy.

Continuous Control Imitation Learning +3

Sample Efficient Social Navigation Using Inverse Reinforcement Learning

no code implementations18 Jun 2021 Bobak H. Baghi, Gregory Dudek

In this paper, we present an algorithm to efficiently learn socially-compliant navigation policies from observations of human trajectories.

reinforcement-learning Reinforcement Learning (RL) +1

Scalable Multirobot Planning for Informed Spatial Sampling

no code implementations20 May 2021 Sandeep Manjanna, M. Ani Hsieh, Gregory Dudek

This paper presents a distributed scalable multi-robot planning algorithm for informed sampling of quasistatic spatial fields.

Autonomous Vehicles

Learning Intuitive Physics with Multimodal Generative Models

1 code implementation12 Jan 2021 Sahand Rezaei-Shoshtari, Francois Robert Hogan, Michael Jenkin, David Meger, Gregory Dudek

Predicting the future interaction of objects when they come into contact with their environment is key for autonomous agents to take intelligent and anticipatory actions.


Learning to Drive Off Road on Smooth Terrain in Unstructured Environments Using an On-Board Camera and Sparse Aerial Images

no code implementations9 Apr 2020 Travis Manderson, Stefan Wapnick, David Meger, Gregory Dudek

We present a method for learning to drive on smooth terrain while simultaneously avoiding collisions in challenging off-road and unstructured outdoor environments using only visual inputs.

One-Shot Informed Robotic Visual Search in the Wild

1 code implementation22 Mar 2020 Karim Koreitem, Florian Shkurti, Travis Manderson, Wei-Di Chang, Juan Camilo Gamboa Higuera, Gregory Dudek

In this paper we propose a method that enables informed visual navigation via a learned visual similarity operator that guides the robot's visual search towards parts of the scene that look like an exemplar image, which is given by the user as a high-level specification for data collection.

Navigate Representation Learning +2

DeepURL: Deep Pose Estimation Framework for Underwater Relative Localization

1 code implementation11 Mar 2020 Bharat Joshi, Md Modasshir, Travis Manderson, Hunter Damron, Marios Xanthidis, Alberto Quattrini Li, Ioannis Rekleitis, Gregory Dudek

In this paper, we propose a real-time deep learning approach for determining the 6D relative pose of Autonomous Underwater Vehicles (AUV) from a single image.

Image-to-Image Translation Pose Estimation +1

Detecting GAN generated errors

no code implementations2 Dec 2019 Xiru Zhu, Fengdi Che, Tianzi Yang, Tzuyang Yu, David Meger, Gregory Dudek

This is because the task of evaluating the quality of a generated image differs from deciding if an image is real or fake.

Reinforcement Learning with Non-uniform State Representations for Adaptive Search

no code implementations15 Jun 2019 Sandeep Manjanna, Herke van Hoof, Gregory Dudek

In this paper, we present a search algorithm that generates efficient trajectories that optimize the rate at which probability mass is covered by a searcher.

reinforcement-learning Reinforcement Learning (RL)

Learning Domain Randomization Distributions for Training Robust Locomotion Policies

no code implementations2 Jun 2019 Melissa Mozifian, Juan Camilo Gamboa Higuera, David Meger, Gregory Dudek

We explore the use of gradient-based search methods to learn a domain randomization with the following properties: 1) The trained policy should be successful in environments sampled from the domain randomization distribution 2) The domain randomization distribution should be wide enough so that the experience similar to the target robot system is observed during training, while addressing the practicality of training finite capacity models.

Planning in Dynamic Environments with Conditional Autoregressive Models

1 code implementation25 Nov 2018 Johanna Hansen, Kyle Kastner, Aaron Courville, Gregory Dudek

We demonstrate the use of conditional autoregressive generative models (van den Oord et al., 2016a) over a discrete latent space (van den Oord et al., 2017b) for forward planning with MCTS.


Scale-Robust Localization Using General Object Landmarks

no code implementations28 Oct 2017 Andrew Holliday, Gregory Dudek

Visual localization under large changes in scale is an important capability in many robotic mapping applications, such as localizing at low altitudes in maps built at high altitudes, or performing loop closure over long distances.

Visual Localization

Underwater Multi-Robot Convoying using Visual Tracking by Detection

1 code implementation25 Sep 2017 Florian Shkurti, Wei-Di Chang, Peter Henderson, Md Jahidul Islam, Juan Camilo Gamboa Higuera, Jimmy Li, Travis Manderson, Anqi Xu, Gregory Dudek, Junaed Sattar

We present a robust multi-robot convoying approach that relies on visual detection of the leading agent, thus enabling target following in unstructured 3-D environments.

object-detection Object Detection +1

Benchmark Environments for Multitask Learning in Continuous Domains

1 code implementation14 Aug 2017 Peter Henderson, Wei-Di Chang, Florian Shkurti, Johanna Hansen, David Meger, Gregory Dudek

As demand drives systems to generalize to various domains and problems, the study of multitask, transfer and lifelong learning has become an increasingly important pursuit.

OpenAI Gym

Modeling Curiosity in a Mobile Robot for Long-Term Autonomous Exploration and Monitoring

no code implementations26 Sep 2015 Yogesh Girdhar, Gregory Dudek

This paper presents a novel approach to modeling curiosity in a mobile robot, which is useful for monitoring and adaptive data collection tasks, especially in the context of long term autonomous missions where pre-programmed missions are likely to have limited utility.

Gibbs Sampling Strategies for Semantic Perception of Streaming Video Data

no code implementations10 Sep 2015 Yogesh Girdhar, Gregory Dudek

Topic modeling of streaming sensor data can be used for high level perception of the environment by a mobile robot.

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