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07/21/2023
GP-Frontier for Local Mapless Navigation
We propose a new frontier concept called the Gaussian Process Frontier (...
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07/08/2023
GP-guided MPPI for Efficient Navigation in Complex Unknown Cluttered Environments
Robotic navigation in unknown, cluttered environments with limited sensi...
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06/26/2023
Pseudo-Trilateral Adversarial Training for Domain Adaptive Traversability Prediction
Traversability prediction is a fundamental perception capability for aut...
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06/16/2023
Multi-Objective and Model-Predictive Tree Search for Spatiotemporal Informative Planning
Adaptive sampling and planning in robotic environmental monitoring are c...
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06/11/2023
Long-Term Autonomous Ocean Monitoring with Streaming Samples
In the autonomous ocean monitoring task, the sampling robot moves in the...
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06/02/2023
Adaptive Robotic Information Gathering via Non-Stationary Gaussian Processes
Robotic Information Gathering (RIG) is a foundational research topic tha...
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03/05/2023
IDA: Informed Domain Adaptive Semantic Segmentation
Mixup-based data augmentation has been validated to be a critical stage ...
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03/05/2023
SePaint: Semantic Map Inpainting via Multinomial Diffusion
Prediction beyond partial observations is crucial for robots to navigate...
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01/26/2023
Light-Weight Pointcloud Representation with Sparse Gaussian Process
This paper presents a framework to represent high-fidelity pointcloud se...
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09/23/2022
UAV-miniUGV Hybrid System for Hidden Area Exploration and Manipulation
We propose a novel hybrid system (both hardware and software) of an Unma...
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05/13/2022
AK: Attentive Kernel for Information Gathering
Robotic Information Gathering (RIG) relies on the uncertainty of a proba...
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04/20/2022
CALI: Coarse-to-Fine ALIgnments Based Unsupervised Domain Adaptation of Traversability Prediction for Deployable Autonomous Navigation
Traversability prediction is a fundamental perception capability for aut...
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03/30/2022
Autonomous Navigation of AGVs in Unknown Cluttered Environments: log-MPPI Control Strategy
Sampling-based model predictive control (MPC) optimization methods, such...
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03/24/2022
Model-Agnostic Multi-Agent Perception Framework
Existing multi-agent perception systems assume that every agent utilizes...
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11/05/2021
Artificial Neural Network-Based Voltage Control of DC/DC Converter for DC Microgrid Applications
The rapid growth of renewable energy technology enables the concept of m...
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11/02/2021
Pareto Monte Carlo Tree Search for Multi-Objective Informative Planning
In many environmental monitoring scenarios, the sampling robot needs to ...
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11/02/2021
Informative Planning in the Presence of Outliers
Informative planning seeks a sequence of actions that guide the robot to...
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10/29/2021
NSS-VAEs: Generative Scene Decomposition for Visual Navigable Space Construction
Detecting navigable space is the first and also a critical step for succ...
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10/29/2021
Efficient Map Prediction via Low-Rank Matrix Completion
In many autonomous mapping tasks, the maps cannot be accurately construc...
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10/29/2021
Multi-Objective Autonomous Exploration on Real-Time Continuous Occupancy Maps
Autonomous exploration in unknown environments using mobile robots is th...
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10/29/2021
Polyline Based Generative Navigable Space Segmentation for Autonomous Visual Navigation
Detecting navigable space is a fundamental capability for mobile robots ...
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10/15/2021
An Artificial Neural Network-Based Model Predictive Control for Three-phase Flying Capacitor Multi-Level Inverter
Model predictive control (MPC) has been used widely in power electronics...
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10/13/2020
Swarming of Aerial Robots with Markov Random Field Optimization
Swarms are highly robust systems that offer unique benefits compared to ...
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06/03/2020
Kernel Taylor-Based Value Function Approximation for Continuous-State Markov Decision Processes
We propose a principled kernel-based policy iteration algorithm to solve...
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05/22/2019
Reachable Space Characterization of Markov Decision Processes with Time Variability
We propose a solution to a time-varying variant of Markov Decision Proce...
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03/04/2019
Creating Navigable Space from Sparse Noisy Map Points
We present a framework for creating navigable space from sparse and nois...
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03/03/2019
State-Continuity Approximation of Markov Decision Processes via Finite Element Analysis for Autonomous System Planning
Motion planning under uncertainty for an autonomous system can be formul...
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02/15/2019
AutoQB: AutoML for Network Quantization and Binarization on Mobile Devices
In this paper, we propose a hierarchical deep reinforcement learning (DR...
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01/04/2019
Accelerating Goal-Directed Reinforcement Learning by Model Characterization
We propose a hybrid approach aimed at improving the sample efficiency in...
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01/04/2019
Solving Markov Decision Processes with Reachability Characterization from Mean First Passage Times
A new mechanism for efficiently solving the Markov decision processes (M...
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01/03/2019
Reachability and Differential based Heuristics for Solving Markov Decision Processes
The solution convergence of Markov Decision Processes (MDPs) can be acce...
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03/11/2018
Learning Partially Structured Environmental Dynamics for Marine Robotic Navigation
We investigate the scenario that a robot needs to reach a designated goa...
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11/24/2016
A Spatio-Temporal Representation for the Orienteering Problem with Time-Varying Profits
We consider an orienteering problem (OP) where an agent needs to visit a...
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09/24/2016