Lucas de Andrade Both
RWTH Aachen University, Fraunhofer Institute for Laser Technology
Papers
2
Total Citations
6
H-Index
2
About
Lucas de Andrade Both is a robotics researcher focused on advancing motion planning and control for industrial automation. His work centers on trajectory optimization for kinematic constrained systems, with direct applications to manufacturing tasks like pick-and-place, welding, and material handling. In his 2023 paper, cited 4 times, he introduced a novel trajectory planning approach with motion duration control, addressing the fundamental challenge of moving a system from an initial to a target state while respecting kinematic limits—a problem critical to enhancing production efficiency. More recently, in 2024, Both explored model-based reinforcement learning for robot-based laser material processing, a domain demanding high-precision motion. His work demonstrates that reinforcement learning can overcome the trajectory accuracy limitations of traditional methods, offering a promising path for articulated robotic arms in advanced manufacturing. With 2 citations already, this research signals growing interest in his innovative fusion of learning-based and classical control techniques. Both’s contributions bridge theory and practice, providing engineers with tools to improve robotic performance in real-world industrial settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2