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Fast and Flexible Sampling-Based Local Replanning for Single-Query Paths in Unknown Environments

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Fast and Flexible Sampling-Based Local Replanning for Single-Query Paths in Unknown Environments

Ros Maria E. F. Stanly et al · LibraryPress@UF · 2026 · ISSN 2334-0754

Path planning in unknown environments remains a challenging research problem in autonomous robotics. Although single-query path planning algorithms such as Rapidly-exploring Random Trees (RRT) and its variants have been ...

LCC TENDOlRlY2hub2xvZ3k~; LCC:Electronic computers. Computer scienceIdioma English

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Adaptive deep reinforcement learning-based control strategy for high-performance permanent magnet synchronous motor drive systems

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Adaptive deep reinforcement learning-based control strategy for high-performance permanent magnet synchronous motor drive systems

S. Dukkipati et al · National Technical University "Kharkiv Polytechnic Institute" · 2026 · ISSN 2074-272X

Introduction. In recent days, electric vehicles, robotics and in many control system applications, permanent magnet synchronous motors (PMSMs) are widely utilized. Problem. Due to non-linear behavior of system, external ...

LCC LCC:Electrical engineering. Electronics. Nuclear engineeringIdioma English

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WGANVO: Odometría visual monocular basada en redes adversarias generativas

Article

WGANVO: Odometría visual monocular basada en redes adversarias generativas

Cremona, Javier Alejandro et al · Comité Español de Automática · 2021 · ISSN 1697-7912

Los sistemas tradicionales de odometría visual (VO), directos o basados en características visuales, son susceptibles de cometer errores de correspondencia entre imágenes. Además, las configuraciones monoculares sól...

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Wildfire detection in large-scale environments using force-based control for swarms of UAVs

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Wildfire detection in large-scale environments using force-based control for swarms of UAVs

Tzoumas, Georgios et al · Springer · 2023 · ISSN 1935-3812

Wildfres afect countries worldwide as global warming increases the probability of their appearance. Monitoring vast areas of forests can be challenging due to the lack of resources and information. Additionally, early de...

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A Multi-Stage Time-Variant Motion Planner for Agile Autonomous Driving Maneuvers

Article

A Multi-Stage Time-Variant Motion Planner for Agile Autonomous Driving Maneuvers

Alexander Langmann et al · IEEE · 2026 · ISSN 2687-7813

Agile, dynamic, and safe motion planning in interactive environments is a key challenge for autonomous vehicles. Most research has focused on enhancing established planning algorithms, often aiming to improve optimality ...

LCC LCC:Transportation engineering; TENDOlRyYW5zcG9ydGF0aW9uIGFuZCBjb21tdW5pY2F0aW9ucw~~Idioma English

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