Results 171 to 180 of about 50,488 (298)

Autonomous Navigation in Large‐Scale Underground Environments Based on a Purely Topological Understanding of Tunnel Networks

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT This work presents a non‐geometrical navigation approach based on a purely topological understanding of underground environments. By conceptualizing subterranean scenarios as a set of tunnels that intersect with each other, and taking a navigation approach based on topological instructions, we simplify the navigation problem to the sequential ...
Lorenzo Cano   +2 more
wiley   +1 more source

A Novel Crawling Robot Based on the Hexagonal Mesh Structure and Enhanced PID Control Strategy

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT The locomotion of crawling robots is similar to that of caterpillars, relying on foot adhesion and body contraction to ensure flexible movement without compromising stability. However, most existing pneumatic soft crawling robots are incapable of simultaneously achieving forward, backward, turning, and climbing capabilities.
Meng Hongjun   +4 more
wiley   +1 more source

Enabling Under Ice Glider Operations: A Backseat Driver Approach

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT Polar Oceans are key locations for forcing global ocean circulation, influencing both global climate and biogeochemical cycles. Due to restricted access to these seasonally and perennially ice‐covered regions, these areas are severely undersampled.
Yaomei Wang   +12 more
wiley   +1 more source

Virtual Elastic Tether: A New Approach for Multi‐Agent Navigation in Confined Aquatic Environments

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT Underwater navigation is a challenging area in the field of mobile robotics due to inherent constraints in self‐localization and communication in underwater environments. Some of these challenges can be mitigated by using collaborative multi‐agent teams.
Kanzhong Yao   +5 more
wiley   +1 more source

Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi   +3 more
wiley   +1 more source

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