Luai Abuelsamen

Luai Abuelsamen

Robotics Master's Student, UC Berkley

Luai Abuelsamen

Hi! I鈥檓 a Master鈥檚 student in Robotics at UC Berkeley working on embodied AI systems that bridge foundation models with real-world control. My research spans from multimodal perception for robot manipulation to large-scale autonomous systems simulation.

Currently, I work as a Graduate Student Researcher at PATH, building traffic simulation tools to evaluate infrastructure impacts on autonomous vehicle behavior. I also collaborate with the Autonomy, Robotics, and Controls (ARC) Lab on manipulation research combining learning-based control with multimodal perception.

Previously, I studied Mechanical Engineering at McGill University and interned at Tesla, Beta Technologies, and Vention, where I worked on embedded systems, mechatronic design, and simulation tooling for robotic platforms.

Research Interests:

  • Foundation models for robotics and embodied AI
  • Multimodal perception and imitation learning
  • Model-based and learning-based control
  • Sim-to-real transfer and real-time planning
  • Multi-agent systems and intelligent infrastructure
Multimodal Imitation Learning

Multimodal Perception in Imitation Learning

Research collaboration analyzing how RGB-D, proprioceptive, and language inputs affect sample complexity and optimization landscapes in robot manipulation tasks, with theoretical insights and empirical validation.

馃搫 Paper 路 馃敆 Code

Industrial Robot Motion Planning

Industrial Robot Motion Planning with GPUs

Integrated NVIDIA cuRobo into modular automation systems for real-time, collision-free trajectory planning in multi-axis robotic platforms, achieving significant speedups for industrial applications.

馃敆 Code 路 馃搫 Paper

PATH Simulation

Autonomous Vehicle Infrastructure Impact Study

Funded research position developing microsimulation models using Aimsun Next to assess freeway auxiliary lane removal impacts on mainline and arterial flows in mixed autonomy scenarios.

馃搫 Paper (submitted to TRB)

Coverage Control

Coverage Control for Hybrid Aerial / Ground Robot Teams

Developed a two-layer Voronoi-based approach for multi-agent coverage in heterogeneous robot teams, improving emergency response coordination and resilience to sensor loss.

馃敆 Code 路 馃搫 Paper

Rocket Landing Optimization

Rocket Landing Trajectory Optimization

Implemented SOCP-based convex optimization in Python for soft landing guidance, accounting for vehicle dynamics, control limits, and environmental constraints with real-time performance.

馃敆 Code 路 馃搫 Report

LLM Drone Control

LLM-Based Natural Language Drone Control

Rapid prototyping project integrating vision-language models, SLAM, and zero-shot action chunking for voice-controlled quadrotor navigation in real environments. Built for Eric Schmidt AI hackathon.

馃敆 Code 路 馃帴 Video

Motor Controller Pi-Hat

PCB Design: Raspberry Pi Motor Controller Hat

Custom PCB enabling high-current servo control and force sensing for autonomous robots, with integrated power regulation and I虏C multiplexing for research platform development.

馃敆 Project Page