A Breadcrumb System for Assisting Outdoor Autonomous Robots with Path Identification and Localization

Grabowsky, David P.; Conrad, James M.; Browne, Aidan F.

doi:10.1109/southeastcon45413.2021.9401846

SoutheastCon 2021 2021

DOI: 10.1109/southeastcon45413.2021.9401846

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A Breadcrumb System for Assisting Outdoor Autonomous Robots with Path Identification and Localization

David P. Grabowsky

James M. Conrad

Aidan F. Browne

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2022

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Cited by 2 publications

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A Robust and Fast Occlusion-based Frontier Method for Autonomous Navigation in Unknown Cluttered Environments

Mohammad

Bezzo

2022

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Robotic navigation in unknown, cluttered environments with limited sensing capabilities poses significant challenges in robotics. Local trajectory optimization methods, such as Model Predictive Path Intergal (MPPI), are a promising solution to this challenge. However, global guidance is required to ensure effective navigation, especially when encountering challenging environmental conditions or navigating beyond the planning horizon. This study presents the GP-MPPI, an online learning-based control strategy that integrates MPPI with a local perception model based on Sparse Gaussian Process (SGP).The key idea is to leverage the learning capability of SGP to construct a variance (uncertainty) surface, which enables the robot to learn about the navigable space surrounding it, identify a set of suggested subgoals, and ultimately recommend the optimal subgoal that minimizes a predefined cost function to the local MPPI planner. Afterward, MPPI computes the optimal control sequence that satisfies the robot and collision avoidance constraints. Such an approach eliminates the necessity of a global map of the environment or an offline training process. We validate the efficiency and robustness of our proposed control strategy through both simulated and real-world experiments of 2D autonomous navigation tasks in complex unknown environments, demonstrating its superiority in guiding the robot safely towards its desired goal while avoiding obstacles and escaping entrapment in local minima. The GPU implementation of GP-MPPI, including the supplementary video, is available at https://github.com/IhabMohamed/GP-MPPI.

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A Robust and Fast Occlusion-based Frontier Method for Autonomous Navigation in Unknown Cluttered Environments

Mohammad

Bezzo

2022

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Machine Learning for Wireless Distance Estimation Model Parameter Estimation for Breadcrumb Localization Applications

2022

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A Breadcrumb System for Assisting Outdoor Autonomous Robots with Path Identification and Localization

Cited by 2 publications

References 15 publications

A Robust and Fast Occlusion-based Frontier Method for Autonomous Navigation in Unknown Cluttered Environments

A Robust and Fast Occlusion-based Frontier Method for Autonomous Navigation in Unknown Cluttered Environments

Machine Learning for Wireless Distance Estimation Model Parameter Estimation for Breadcrumb Localization Applications

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