The KAUST Robotics, Intelligent Systems, and Control Lab (KAUST RISC Lab) focuses on all aspects of robotics and embedded intelligence. RISC is engaged in a variety of projects involving intelligent autonomous systems either acting alone or within a distributed decision architecture with other autonomous agents and/or human actors. Representative topics of interest include aerial operations, underwater mapping and manipulation, robotic self-maintenance and regeneration, safe intelligence, and intelligent prothesis design.

Our research follows the broad themes of:

  • Autonomy: Design of robotic systems with onboard intelligence to operate in complex environments with limited human supervision.
  • Distributed Autonomy: Self-organization and adaptation of multi-agent autonomous systems and swarms.
  • Humans & Machines:  Systems where humans and robots collaborate.
  • Robotic technologies: positioning, actuation, computer architectures, software engineering, cybernetics, and artificial intelligence.


We invite you to visit our YouTube Channel to watch the recordings of the talks from the KAUST Research Conference on Robotics and Autonomy (#RobotoKAUST).
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RISC logo adapted from RetroTech font by tcolson and licensed under CC BY-NC-SA 3.0 US.

Principal Investigators

RISC Lab Shinkyu Park 4530

Shinkyu Park

Assistant Professor, Electrical and Computer Engineering
shinkyu.park [at] kaust.edu.sa
https://orcid.org/0000-0002-8643-404X
KAUST RISC Lab
Shinkyu Park is an Assistant Professor of Electrical Engineering and the PI of Distributed Systems and Autonomy Lab. Park’s research group focuses on learning, planning, and control in multi-robot systems. They aim to build individual robots’ core capabilities of sensing, actuation, and communication and to train them to learn the ability to work as a team and attain high-level of autonomy in distributed information processing, decision making, and manipulation. The group applies ML/AI methods to process sensor data to allow robots to perceive and interact with surrounding environments, and to implement computational models for robot decision making demonstrating high-level autonomy and social behavior. They are applying research outcomes to applications in environmental monitoring, factory automation, and service robotics.