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== '''IARA's Specifications''' ==
 
== '''IARA's Specifications''' ==
IARA is an experimental robotic platform, based on a Ford Escape Hybrid (Fig. 5(a)). It has several high-end sensors, including: two Point Grey Bumblebee XB3 stereo cameras and two Point Grey Bumblebee 2 stereo cameras, one Light Detection and Ranging (LIDAR) Velodyne HDL 32-E, and one GPS-aided Attitude and Heading Reference System (AHRS/GPS) Xsens MTiG (Fig. 5(b)). To process the data coming from the sensors, the platform can hold up to four Dell Precision R5500 (2 Intel Xeon 2.13 GHZ, 12 GB RAM, 2 HDs SSD of 120GB on RAID0 and GPU cards Tesla C2050) (two installed in the configuration shown in Fig. 5(b)). We implemented many software modules for IARA that currently allows for its autonomous operation, such as modules for mapping, localization, behavior selection, path following, control, and motion planning (that is the focus of this paper). We also implemented a software module for autonomous vehicle simulation to help in the development and testing of all the other IARA’s modules (that was used to evaluate the performance of the motion planner presented in this paper). See video of IARA autonomous operation at [http://youtu.be/4rFCjrFdR7o] and videos about other IARA’s software modules at [http://www.youtube.com/user/lcadufes].
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IARA is an experimental robotic platform, based on a Ford Escape Hybrid (Fig. 5(a)). It has several high-end sensors, including: two Point Grey Bumblebee XB3 stereo cameras and two Point Grey Bumblebee 2 stereo cameras, one Light Detection and Ranging (LIDAR) Velodyne HDL 32-E, and one GPS-aided Attitude and Heading Reference System (AHRS/GPS) Xsens MTiG (Fig. 5(b)). To process the data coming from the sensors, the platform can hold up to four Dell Precision R5500 (2 Intel Xeon 2.13 GHZ, 12 GB RAM, 2 HDs SSD of 120GB on RAID0 and GPU cards Tesla C2050) (two installed in the configuration shown in Fig. 5(b)). We implemented many software modules for IARA that currently allows for its autonomous operation, such as modules for mapping, localization, behavior selection, path following, control, and motion planning (that is the focus of this paper). We also implemented a software module for autonomous vehicle simulation to help in the development and testing of all the other IARA’s modules (that was used to evaluate the performance of the motion planner presented in this paper). See video of IARA autonomous operation at [https://www.youtube.com/watch?v=zE7np6tgCHc&list=UUsQuY9t5ss3jwHBiRaEEFFg] and videos about other IARA’s software modules at [http://www.youtube.com/user/lcadufes].
  
 
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Edição das 09h20min de 20 de novembro de 2014

Inteligent Autonomous Robotic Automobile - IARA

About IARA

A team of students and researchers of the Laboratório de Computação de Alto Desempenho (High-Performance Computing Laboratory) of Universidade Federal do Espírito Santo (Federal University of Espírito Santo), leaded by Professor Alberto F. De Souza, designed and built one of the first autonomous cars of Brazil. Christened IARA (Intelligent Autonomous Robotic Automobile), this autonomous car was able to run autonomously for tens of kilometers at speeds of up to of 30 Km/h in urban roads surrounding the main campus of UFES (See video at [1]).

IARA's Specifications

IARA is an experimental robotic platform, based on a Ford Escape Hybrid (Fig. 5(a)). It has several high-end sensors, including: two Point Grey Bumblebee XB3 stereo cameras and two Point Grey Bumblebee 2 stereo cameras, one Light Detection and Ranging (LIDAR) Velodyne HDL 32-E, and one GPS-aided Attitude and Heading Reference System (AHRS/GPS) Xsens MTiG (Fig. 5(b)). To process the data coming from the sensors, the platform can hold up to four Dell Precision R5500 (2 Intel Xeon 2.13 GHZ, 12 GB RAM, 2 HDs SSD of 120GB on RAID0 and GPU cards Tesla C2050) (two installed in the configuration shown in Fig. 5(b)). We implemented many software modules for IARA that currently allows for its autonomous operation, such as modules for mapping, localization, behavior selection, path following, control, and motion planning (that is the focus of this paper). We also implemented a software module for autonomous vehicle simulation to help in the development and testing of all the other IARA’s modules (that was used to evaluate the performance of the motion planner presented in this paper). See video of IARA autonomous operation at [2] and videos about other IARA’s software modules at [3].

Intelligent Autonomous Robotic Automobile - IARA
Inside IARA's cockpit
Intelligent Autonomous Robotic Automobile - IARA Inside IARA's cockpit

Our team

Our team is lead by Dr. Alberto Ferreira De Souza from the High Performance Computing Laboratory (LCAD) of the Federal University of Espirito Santo (UFES). The LCAD/UFES lab is located in the city of Vitoria, Brazil, and congregates several professors and students working on artificial vision, face recognition, autonomous vehicles and humanoid robot researches. To learn more about our team see LCAD/UFES member list)

LCAD/UFES team and IARA autonomous vehicle
LCAD/UFES team and IARA autonomous vehicle