Control, robotics, planning, and learning
Robotics for safer collaboration, smarter automation, and sustainable manufacturing.
The Control and Robotics Lab at Texas A&M develops planning, control, learning, and prediction methods that help robots work with people in complex real-world environments.
Research themes
We build intelligent robotic systems that reason, adapt, and work around people.
Human-Robot Collaboration
Prediction, planning, and safety-aware control for robots operating near people.
Robotic Disassembly & Recycling
Collaborative robotic systems for end-of-use product disassembly, remanufacturing, and e-waste recovery.
Learning-Based Planning
Neural motion planners, spatial reasoning, and generalist manipulation methods for robot arms.
Control of Dynamic Systems
Robust and learning-enabled control for aerial robots, connected vehicles, and precision systems.
Featured direction
Human-aware robotics for disassembly, recycling, and remanufacturing.
Our work increases the capacity of robotics in labor-intensive disassembly by creating collaborative environments between humans and robots with safety, efficiency, and operational cost in mind.
Recent highlights
Latest from the lab
February 19, 2026
Generalist neural motion planners for robotic manipulators
Our T-ASE survey maps deep learning approaches to planning primitives and identifies challenges in generalization, safety, and real-time deployment.
October 29, 2025
RAISE for end-of-life phone disassembly
A robot-assisted selective disassembly and sorting system for scalable, cost-effective electronics recycling.
June 5, 2025
Three papers presented at ICRA 2025
The lab presented recent work in robotic motion planning and manipulation at IEEE ICRA.
Opportunities
Interested in robotics research?
We welcome motivated students and researchers with interests in robotics, control, planning, optimization, machine learning, mechatronics, and human-robot collaboration.