Results 21 to 30 of about 309,612 (268)

MAT-Fly: An Educational Platform for Simulating Unmanned Aerial Vehicles Aimed to Detect and Track Moving Objects

open access: yesIEEE Access, 2021
The main motivation of this work is to propose a simulation approach for a specific task within the Unmanned Aerial Vehicle (UAV) field, i.e., the visual detection and tracking of arbitrary moving objects.
Giuseppe Silano, Luigi Iannelli
doaj   +1 more source

Speed Law Control in Some Tasks for Underwater Vehicles

open access: yesСовременные информационные технологии и IT-образование, 2019
The article deals with two tasks of providing the rear motion of autonomous underwater vehicles. The first task is to find the paths with specific yaw angle along the given set of target points in the plane.
Nataliia A. Zhabko   +4 more
doaj   +1 more source

Computation Offloading and Trajectory Control for UAV-Assisted Edge Computing Using Deep Reinforcement Learning

open access: yesApplied Sciences, 2022
Task offloading has attracted widespread attention in accelerating applications and reducing energy consumption. However, in areas with surging traffic (nucleic acid testing, concerts, etc.), the limited resources of fixed-base stations cannot meet user ...
Huamei Qi, Zheng Zhou
doaj   +1 more source

Trajectory Control Strategy and System Modeling of Load-Sensitive Hydraulic Excavator

open access: yesMachines, 2022
Accurate control of excavator trajectory is the foundation for the intelligent and unmanned development of excavators. The excavator operation process requires multiple actuators to cooperate to complete the response action. However, the existing control
Haoju Song   +3 more
doaj   +1 more source

Dynamic Trajectory Control and User Association for Unmanned-Aerial-Vehicle-Assisted Mobile Edge Computing: A Deep Reinforcement Learning Approach

open access: yesDrones
Mobile edge computing (MEC) has become an effective framework for latency-sensitive and computation-intensive applications by deploying computing resources at network edge.
Libo Wang   +6 more
doaj   +1 more source

Machine learning–based robust trajectory tracking control for FSGR

open access: yesThe Journal of Engineering, 2019
Here, a robust adaptive trajectory tracking algorithm is proposed for free-form surface grinding robot (FSGR) in metal surface production line. Machine-learning method is used for robot dynamic approximation which is hard to obtain directly. Adaptive law
Lin Jia   +5 more
doaj   +1 more source

Heavy viable trajectories of controlled systems [PDF]

open access: yesAnnales de l'Institut Henri Poincaré C, Analyse non linéaire, 1985
We define and study the concept of heavy viable trajectories of a controlled system with feedbacks. Viable trajectories are trajectories satisfying at each instant given constraints on the state. The controls regulating viable trajectories evolve according a set-valued feedback map . Heavy
Aubin, J.-P., Frankowska, H.
openaire   +4 more sources

On the force/trajectory control of robot arms

open access: yesAdvanced Robotics, 1986
In the control of a robot arm, it is necessary to control the trajectory of its tip as well as the force which is exerted on the surrounding environment.
CHIDA, Yuichi   +2 more
openaire   +2 more sources

Self‐supervised vessel trajectory segmentation via learning spatio‐temporal semantics

open access: yesIET Intelligent Transport Systems
The study of vessel trajectories (VTs) holds significant benefits for marine route management and resource development. VT segmentation serves as a foundation for extracting vessel motion primitives and enables analysis of vessel manoeuvring habits and ...
Rui Zhang   +5 more
doaj   +1 more source

Finite‐time tracking control of disturbed non‐holonomic systems with input saturation and state constraints: Theory and experiment

open access: yesIET Control Theory & Applications, 2023
This article investigates the finite‐time tracking control problem for disturbed non‐holonomic systems with input saturation and state constraints. Input saturation is ensured by utilizing saturated state feedback and designing auxiliary variables.
Mengmeng Liu, Kang Wu, Yuqiang Wu
doaj   +1 more source

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