Using Kinect on an Autonomous Vehicle for Outdoors Obstacle Detection

Hernández-Aceituno, Javier; Arnay, Rafael; Toledo, Jonay; Sánchez, Leopoldo

doi:10.1109/jsen.2016.2531122

Cited by 48 publications

(22 citation statements)

References 25 publications

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“…[15] developed a hierarchical controller for AVs to track reference paths in uncertain conditions and with external disturbances. [16] designed a method to detect obstacles and dangerous areas in the outdoor environments with Kinect sensors installed on AVs. [17] studied the collective behavior of AV flocking under an all-to-all communication scheme.…”

Section: Related Workmentioning

confidence: 99%

Coordinated Autonomous Vehicle Parking for Vehicle-to-Grid Services: Formulation and Distributed Algorithm

Lam

Hou

et al. 2018

IEEE Trans. Smart Grid

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Autonomous vehicles (AVs) will revolutionarize ground transport and take a substantial role in the future transportation system. Most AVs are likely to be electric vehicles (EVs) and they can participate in the vehicle-to-grid (V2G) system to support various V2G services. Although it is generally infeasible for EVs to dictate their routes, we can design AV travel plans to fulfill certain system-wide objectives. In this paper, we focus on the AVs looking for parking and study how they can be led to appropriate parking facilities to support V2G services. We formulate the Coordinated Parking Problem (CPP), which can be solved by a standard integer linear program solver but requires long computational time. To make it more practical, we develop a distributed algorithm to address CPP based on dual decomposition. We carry out a series of simulations to evaluate the proposed solution methods. Our results show that the distributed algorithm can produce nearly optimal solutions with substantially less computational time. A coarser time scale can improve computational time but degrade the solution quality resulting in possible infeasible solution. Even with communication loss, the distributed algorithm can still perform well and converge with only little degradation in speed.

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Section: Related Workmentioning

confidence: 99%

Coordinated Autonomous Vehicle Parking for Vehicle-to-Grid Services: Formulation and Distributed Algorithm

Lam

Hou

et al. 2018

IEEE Trans. Smart Grid

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“…However, it takes time to install and calibrate the sensors because multiple sensors are used. Reference [ 22 ] examined obstacle detection (convex portion only) using Kinect v2 during the daytime and presented the possibility of obstacle detection by Kinect v2. However, no detailed explanation is available for the detectable range or the detection accuracy of obstacles by Kinect v2 during the daytime.…”

Section: Related Workmentioning

confidence: 99%

Hazardous Object Detection by Using Kinect Sensor in a Handle-Type Electric Wheelchair

Kim

Hasegawa

Sasaki³

2017

Sensors

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To ensure the safety of a handle-type electric wheelchair (hereinafter, electric wheelchair), this paper describes the applicability of using a Kinect sensor. Ensuring the mobility of elderly people is a particularly important issue to be resolved. An electric wheelchair is useful as a means of transportation for elderly people. Considering that the users of electric wheelchairs are elderly people, it is important to ensure the safety of electric wheelchairs at night. To ensure the safety of an electric wheelchair at night, we constructed a hazardous object detection system using commercially available and inexpensive Kinect sensors and examined the applicability of the system. We examined warning timing with consideration to the cognition, judgment, and operation time of elderly people. Based on this, a hazardous object detection area was determined. Furthermore, the detection of static and dynamic hazardous objects was carried out at night and the results showed that the system was able to detect with high accuracy. We also conducted experiments related to dynamic hazardous object detection during daytime. From the above, it showed that the system could be applicable to ensuring the safety of the handle-type electric wheelchair.

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“…Em (Hara et al, 2014),é desenvolvido uma nova ferramenta, chamada de Tohme, que detecta rampas de acesso em meios-fios a partir de imagens extraídas do Google Street View utilizando colaboração coletiva e algoritmos de visão computacional e aprendizado de máquina. Já o trabalho de Hernandez-Aceituno et al (2016) apresenta uma abordagem para a navegação autônoma de veículos que inclui um sensor Kinect para localizaráreas intransponíveis através da detecção e isolação de superfícies não-horizontais, que são consideradas como obstáculos.…”

Section: Introductionunclassified

Detecção e modelagem de rampas para órteses ativas usando uma câmera RGB-D

Santos

Nascimento

Pereira

et al. 2019

Anais Do 14º Simpósio Brasileiro De Automação Inteligente

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This paper presents a ramp detection and modeling algorithm applied in a active orthosis. This method uses depth sensing capacities of the RGB-D cameras to segment different detected planes that integrate the scene and then performs a classification that compares the slope and width of the detected planes with acessibility especifications shown in technical standards. Simulations were made using four different ramps and it proves that the system is able to appropriately classify these structures. Resumo: Este artigo apresenta um novo algoritmo de detecção e modelagem de rampas transponíveis aplicados a umaórtese ativa. Esse método utiliza uma câmera RGB-D que possui a capacidade de obter informações de profundidade dos objetos que estão no ambiente para segmentar diferentes planos detectados que integram a cena e então realiza a classificação comparando a inclinação e a largura dos planos encontrados com especificações de acessibilidade de normas técnicas. A metodologia foi testada por meio de simulações utilizando quatro rampas com características de inclinação e largura distintas. Foi possível constatar que a estratégia empregada foi capaz de classificar os objetos adequadamente.

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Using Kinect on an Autonomous Vehicle for Outdoors Obstacle Detection

Cited by 48 publications

References 25 publications

Coordinated Autonomous Vehicle Parking for Vehicle-to-Grid Services: Formulation and Distributed Algorithm

Coordinated Autonomous Vehicle Parking for Vehicle-to-Grid Services: Formulation and Distributed Algorithm

Hazardous Object Detection by Using Kinect Sensor in a Handle-Type Electric Wheelchair

Detecção e modelagem de rampas para órteses ativas usando uma câmera RGB-D

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