Premium
Robot System of DRC‐HUBO+ and Control Strategy of Team KAIST in DARPA Robotics Challenge Finals
Author(s) -
Lim Jeongsoo,
Lee Inho,
Shim Inwook,
Jung Hyobin,
Joe Hyun Min,
Bae Hyoin,
Sim Okkee,
Oh Jaesung,
Jung Taejin,
Shin Seunghak,
Joo Kyungdon,
Kim Mingeuk,
Lee Kangkyu,
Bok Yunsu,
Choi DongGeol,
Cho Buyoun,
Kim Sungwoo,
Heo Jungwoo,
Kim Inhyeok,
Lee Jungho,
Kwon In So,
Oh JunHo
Publication year - 2017
Publication title -
journal of field robotics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.152
H-Index - 96
eISSN - 1556-4967
pISSN - 1556-4959
DOI - 10.1002/rob.21673
Subject(s) - robotics , artificial intelligence , robot , inverse kinematics , humanoid robot , robustness (evolution) , computer science , software , engineering , robot control , mobile robot , biochemistry , chemistry , gene , programming language
This paper summarizes how Team KAIST prepared for the DARPA Robotics Challenge (DRC) Finals, especially in terms of the robot system and control strategy. To imitate the Fukushima nuclear disaster situation, the DRC performed eight tasks and degraded communication conditions. This competition demanded various robotic technologies, such as manipulation, mobility, telemetry, autonomy, and localization. Their systematic integration and the overall system robustness were also important issues in completing the challenge. In this sense, this paper presents a hardware and software system for the DRC‐HUBO+, a humanoid robot that was used for the DRC; it also presents control methods, such as inverse kinematics, compliance control, a walking algorithm, and a vision algorithm, all of which were implemented to accomplish the tasks. The strategies and operations for each task are briefly explained with vision algorithms. This paper summarizes what we learned from the DRC before the conclusion. In the competition, 25 international teams participated with their various robot platforms. We competed in this challenge using the DRC‐HUBO+ and won first place in the competition.