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Humanoid robot locomotion system with balancing feedback using leg and arm strategy and stepping strategy
a Department of Electrical Engineering, STEI-Institut Teknologi Bandung, Bandung, West Java, 40132, 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]© 2015 IEEE.Humanoid robot must has an ability to move with dynamic motion. Robot is required to walk even get any interference of other robots or other disturbance, and keep its balance. In general, robot motion system is built by 2 kinematics systems, inverse kinematics and forward kinematics. Inverse kinematics is more often used for robot motion because it is more dynamic compare to forward kinematics. Robot motion also has to have a balancing system. In this capstone design, feedback system for robot motion balancing is developed using 2 strategy, leg and arm strategy, and stepping strategy. Leg and arm strategy is a technique to obtain balancing by giving direct feedback to actuator based on Robot Center of Mass (CoM). Stepping is a technique to maintain balance when robot is walking. Stepping is done by making robot motion trajectory to make one of robot’s legs take a charge as robot support. Robot motion balancing algorithm has been implemented in robot platform Baldhart v1.0. Robot has ability to keep its balance with maximum disturbance 25° in 4 directions. Robot has ability to move in a plane with different height for maximum 0.6 cm.[/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]Balancing algorithms,Different heights,Feedback systems,Forward kinematics,Humanoid robot,Humanoid robot locomotion,leg and arm strategy,Stepping strategy[/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]humanoid robot,leg and arm strategy,Stepping strategy[/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][/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/ICEEI.2015.7352579[/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]