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42dot ÀÚÀ² ÁÖÇà ºÐ¾ßÀÇ Control System Engineer ´Â ¿©·¯ µµÀüÀûÀÎ ¹®Á¦¸¦ ÇØ°áÇϱâ À§ÇØ primitive control systems À» °³¹ßÇÏ°Ô µË´Ï´Ù. Motion planning, Functional safety, HW engineering ¹× ±âŸ °ü·Ã ºÐ¾ß Àü¹®°¡µé°ú Çù·ÂÇÏ¿© °ß°íÇÑ ½Ã½ºÅÛÀ» °³¹ßÇÏ´Â µ¥ ±â¿©ÇÒ °ÍÀÔ´Ï´Ù.

As a Control Engineer of 42dot, you will develop primitive control systems to tackle the most challenging problems in autonomous driving. You will contribute towards developing robust systems by collaborating with experts in motion planning, functional safety, HW engineering, and other related disciplines.

Ã¥ÀÓ (RESPONSIBILITIES)

  • ÀÚÀ² ÁÖÇàÀ» À§ÇÑ Á¾¹æÇâ ¹× È¾¹æÇâ Á¦¾î¸¦ ¼³°èÇÏ°í ±¸ÇöÇϸç ÃÖÀûÈ­ÇÕ´Ï´Ù.
  • High-level ÀÇ ¸í·ÉÀ» ½Ç½Ã°£ ÀÚÀ² ÁÖÇà ÀÛ¾÷À» À§ÇÑ ±¸Ã¼ÀûÀÎ actuator Á¦¾î·Î º¯È¯ÇÏ´Â ÇÏÀ§ ¼öÁØ Á¦¾î¸¦ ¼³°èÇÏ°í ±¸ÇöÇÕ´Ï´Ù.
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  • Design, implement, and optimize the longitudinal and lateral control for autonomous driving.
  • Design and implement lower-level controls, translating high-level commands into specific actuator controls for real-time execution of autonomous operations.
  • Develop estimation algorithms for key vehicle parameters such as road slope, vehicle speed, and slip, in order to enhance the precision and reliability of the control system.
  • Work closely with other engineers and teams, such as those focused on motion planning, behavior planning, and mission planning, to ensure seamless.

ÀÚ°Ý¿ä°Ç (QUALIFICATIONS)

  • ·Îº¿°øÇÐ, Àü±â °øÇÐ, ±â°è °øÇÐ, ÄÄÇ»ÅÍ °úÇÐ ¶Ç´Â °ü·Ã ºÐ¾ß¿¡¼­ Çлç/¼®»ç ÇÐÀ§ ¼ÒÁöÀÚ
  • °ü·Ã °æÇè 3³â ÀÌ»ó
  • °­ÀÎÇÑ Á¦¾î (Robust Control), Â÷·® ¿ªÇÐ ¹× ½Ã½ºÅÛ °øÇп¡ ´ëÇÑ ÀÌÇØ¿Í ½Ç¹« °æÇè. ½Ã½ºÅÛ °£¼· °üÂû, ½Ã½ºÅÛ ½Äº° ¹× Ä®¸¸ ÇÊÅÍ ¹× ÀÔÀÚ ÇÊÅÍ¿Í °°Àº »óÅ ÃßÁ¤ ±â¼ú¿¡ ´ëÇÑ °æÇè
  • ±¸Ã¼ÀûÀ¸·Î actuator Á¦¾î¸¦ À§ÇÑ ÇÏÀ§ ¼öÁØ Á¦¾î ½Ã½ºÅÛ¿¡¼­ ÀÔÁõµÈ °æÇè
  • C++, Python ¶Ç´Â µ¿µîÇÑ ¾ð¾î·Î °­·ÂÇÑ ÄÚµù ±â¼úÀ» °¡Áø ¼ÒÇÁÆ®¿þ¾î °³¹ß ´É·Â

  • Bachelor¡¯s/Master's degree in Robotics, Electrical Engineering, Mechanical Engineering, Computer Science, or related field
  • +3 years of related experience
  • Strong understanding and practical experience with robust control, vehicle dynamics, and systems engineering
  • Experience with disturbance observation, system identification, and state estimation techniques such as Kalman filter and Particle filter
  • Proven experience in lower-level control systems, specifically for actuator control
  • Proficiency in software development, with strong coding skills in languages like C++, Python, or equivalent

¿ì´ë»çÇ× (PREFERRED QUALIFICATIONS)

  • ROS/ROS2 °æÇè º¸À¯
  • ¸ðµ¨ ¿¹Ãø Á¦¾î (MPC) ¹× ºñ¼±Çü Á¦¾î ½Ã½ºÅÛ °æÇè
  • ÀÚµ¿Â÷ ¶Ç´Â Ç×°ø¿ìÁÖ ºÐ¾ß¿¡¼­ »ê¾÷ Ç¥ÁØ ¹× ¾ÈÀü Áß¿ä ½Ã½ºÅÛ °æÇè
  • Á¶Á¤ °¡´ÉÇÏ°í ÀÚ°¡ º¸Á¤ Á¦¾î ¾Ë°í¸®ÁòÀ» È°¿ëÇÏ¿© ¹ÙÄû Á¤·Ä°ú °°Àº ´Ù¾çÇÑ ¿î¿µ Á¶°Ç¿¡¼­ ½Ã½ºÅÛ ¼º´ÉÀ» À¯ÁöÇÏ°í Çâ»ó½ÃÅ°´Â °æÇè
  • ¿øº» Á¦¾î °ü¸® (Source Control Management), ºôµå ÇÁ·Î¼¼½º, ÄÚµå ¸®ºä ¹× Å×½ºÆ® ¹æ¹ý °æÇè
  • °ü·Ã ºÐ¾ß¿¡¼­ÀÇ ÃâÆÇ µÈ ¿¬±¸ ÀÛ¾÷À¸·Î ±â¼ú ´É·ÂÀ» Áõ¸íÇÑ °æÇè

  • Experience in ROS/ROS2
  • Experience with Model Predictive Control (MPC) and Nonlinear Control Systems
  • Experience with industry standards and safety-critical systems in automotive or aerospace domains
  • Experience in leveraging adaptive, self-calibrating control algorithms to maintain and improve system performance under varying operating conditions, such as misaligned wheel alignment
  • Experience with source control management, build processes, code reviews, and testing methods
  • Published research work in relevant fields demonstrating technical proficiency

ÀüÇü ÀýÂ÷ (INTERVIEW PROCESS)

  • ¼­·ùÀüÇü - È­»ó¸éÁ¢ (1½Ã°£ ³»¿Ü) - ´ë¸é ȤÀº È­»ó¸éÁ¢ (3½Ã°£ ³»¿Ü) - ÃÖÁ¾ÇÕ°Ý
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  • KCCV 2022 ¹× UMOS Day 2021 - ÀÚÀ²ÁÖÇà AI ¼ÒÇÁÆ®¿þ¾î AKit Core ¿µ»ó



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