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Design of obstacle avoidance system on hexacopter using vector field histogram-plus

Sary I.P.a, Nugraha Y.P.a, Megayanti M.a, Hidayat E.a, Trilaksono B.R.a

a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 IEEE.Contaminated areas of hazardous chemicals, radioactive and nuclear (CRN) can be known through the survey process with the help of operators so that technology solutions are offered to replace the operator’s task, namely the Unmanned Aerial Vehicle. One type of Unmanned Aerial Vehicle is Hexacopter which is designed with an autonomous control system. Hexacopter requires the ability to obstacle avoidance in conducting survey missions in contaminated areas. The algorithm is used to obstacle avoidance is the vector field histogram-plus (VFH+). The VFH+ algorithm processes data input from distance measurement to the steering angle. The steering angles resulting from the calculation of the VFH+ algorithm is used to obstacle avoidance. Measurement of distance between object and Hexacopter using lidar sensor. In this research, the design of the obstacle avoidance system is tested in the gazebo environment running on the ROS system. The VFH+ algorithm test is done by placing obstacles on the path to be passed by the Hexacopter, so VFH+ will produce a steering angle to obstacle avoidance in accordance with the specification of the safe distance that can be passed and headed to the desired position.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Autonomous control systems,Contaminated areas,Gazebo,Hazardous chemicals,Hexacopter,Obstacle-avoidance system,Technology solutions,Vector field histograms[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Gazebo,Hexacopter,Obstacle avoidance,ROS,VFH+[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]ACKNOWLEDGMENT This work was partially funded by The Ministry of Research, Technology and Higher Education, Republic of Indonesia through the PUSNAS 2017 Program.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICSEngT.2018.8606388[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]