Integration of Vision and LIDAR for Navigation of Micro Aerial Vehicle

Sakthivel, P.; Anbarasu, B.

doi:10.1109/mpcit51588.2020.9350494

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…Updating the position of the obstacles the control commands will be changed and consequently, the path followed by the platform will be different. The challenge of identifying the position and size of an obstacle can be tackled by various methods like [29] or [30]. Finally, this method is designed to support cylindrical obstacles but it can be extended to different shapes with a similar formulation as the one presented in Section 3.3.1.…”

Section: Multi-stage Nmpcmentioning

confidence: 99%

Multi-Stage NMPC for a MAV based Collision Free Navigation Under Varying Communication Delays

Papadimitriou

Jafari²,

Mansouri³

et al. 2023

J Intell Robot Syst

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Time delays in communication networks are one of the main concerns in deploying robots with computation boards on the edge. This article proposes a multi-stage Nonlinear Model Predictive Control (NMPC) that is capable of handling varying network-induced time delays for establishing a control framework being able to guarantee collision-free Micro Aerial Vehicles (MAVs) navigation. This study introduces a novel approach that considers different sampling times by a tree of discretization scenarios contrary to the existing typical multi-stage NMPC where system uncertainties are modeled by a tree of scenarios. Additionally, the proposed method considers adaptive weights for the multi-stage NMPC scenarios based on the probability of time delays in the communication link. As a result of the multi-stage NMPC, the obtained optimal control action is valid for multiple sampling times. Finally, the overall effectiveness of the proposed novel control framework is demonstrated in various tests and different simulation environments.

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Section: Multi-stage Nmpcmentioning

confidence: 99%

Multi-Stage NMPC for a MAV based Collision Free Navigation Under Varying Communication Delays

Papadimitriou

Jafari²,

Mansouri³

et al. 2023

J Intell Robot Syst

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“…Pada paper ini, dilakukan uji coba pada perputaran motor listrik. Selain menggunakan sensor A3144, dapat juga menggunakan sensor MPU-9250 [22], [23] atau sensor AK8963 [22]. Gambar 15.…”

Section: Menggunakan Sensorunclassified

Review Aplikasi Sensor Pada Sistem Monitoring Dan Kontrol Berbasis Mikrokontroler Arduino

Anantajaya¹,

Kumara²,

Divayana³

2022

SPEKTRUM

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Arduino microcontrollers have been widely used in research and society. The Arduino isequipped with one or more physical sensors to convert physical quantities into electrical signalsthat can be processed by the microcontroller. This paper reviews sensors, types of Arduino, andtheir application as a monitoring system. Data were obtained from platforms discussing onlineArduino projects, scientific articles, electronic/micro-electronic component manufacturer sites,and other reliable sources. The results show that the sensors that are commonly used includetemperature and humidity sensors DHT11, DHT22, Thermistor and LM35, limit switch touchsensors, proximity sensors HC-SR04, and Paralax PIR, gas sensors MQ2, MQ3, MQ5, MQ6,MQ7, MQ8, and MQ135 correspond to detected gases, ADXL345 and A3144 acceleration andmagnet sensors, TCS3200 and TCS 34752 color sensors, KY-026 and Robotdyn IR firesensors, KY-022 and KY-005 Infrared sensors, LDR and TSL2561 light sensors, voltage-currentsensors ACS712 and PZEM-004T, and heart rate sensors KY-039 and MAX30102. While themicrocontrollers that are often used include Arduino Uno, Arduino Nano, Arduino Mega, andother microcontrollers. Applications that have been developed include applications in the fieldsof health, agriculture and farm, creation of robots, security to vehicles.

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Unveiling the Shadows: Leveraging Current Drone Detection Vulnerabilities to Design and Build a Stealth Drone

Ahmed,

Qassmi,

Fatima Rizvi

et al. 2024

2024 2nd International Conference on Unmanned Vehicle Systems-Oman (UVS)

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Integration of Vision and LIDAR for Navigation of Micro Aerial Vehicle

Cited by 3 publications

References 15 publications

Multi-Stage NMPC for a MAV based Collision Free Navigation Under Varying Communication Delays

Multi-Stage NMPC for a MAV based Collision Free Navigation Under Varying Communication Delays

Review Aplikasi Sensor Pada Sistem Monitoring Dan Kontrol Berbasis Mikrokontroler Arduino

Unveiling the Shadows: Leveraging Current Drone Detection Vulnerabilities to Design and Build a Stealth Drone

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