Resmana Lim

About

Resmana Lim is a leading researcher in the intersection of brain-computer interfaces (BCI) and autonomous mobile robotics. His pioneering work demonstrates how EEG signals can directly control robotic systems, most notably in his 2018 study on using the Emotiv Epoc+ headset to navigate an RC car—a project that has garnered 6 citations for its innovative integration of consumer-grade EEG hardware with ESP8266 microcontrollers. Lim has also made significant contributions to intelligent navigation, developing an Interval Type-2 Fuzzy Logic Controller for obstacle avoidance in telepresence robots (2014) and advancing odometry algorithms for mobile robot navigation (2016). His research extends to autonomous driving platforms, including work on traffic light recognition for Duckietown’s self-driving Duckiebots. With a focus on making robotic control accessible through non-invasive brain sensing and robust autonomous algorithms, Lim’s work has laid foundational groundwork for assistive technologies and intelligent transport systems. His studies consistently bridge theoretical control systems with practical, real-world robotic applications, earning him recognition as a key figure in Southeast Asian robotics and BCI research.

Research Focus

Key Achievements

Top Papers

1. 1
   Brain Computer Interface for Controlling RC-Car Using Emotiv Epoc+

   6 citations · 2018
2. 2
   Obstacles Avoidance for Intelligent Telepresence Robot Using Interval Type-2 FLC

   3 citations · 2014
3. 3
   Odometry Algorithm with Obstacle Avoidance on Mobile Robot Navigation

   3 citations · 2016
4. 4
   Pengenalan Traffic Light Pada Robot Mobil Duckietown

   3 citations · 2018
5. 5
   A Study of Mobile Robot Control using EEG Emotiv Epoch Sensor

   2 citations · 2018

Key Collaborators

Contact & Links