Industrial robots are traditionally programmed for speed, accuracy, and repeatability, but growing interest in energy efficiency, sustainability, and operational cost reduction has created a demand for energy‑aware planning techniques. Meanwhile, industrial CAD data (parts, contours, manufacturing paths) provides a rich and reusable source of trajectory information — yet transforming CAD geometry into optimized robot motion remains a lergely open development task.

This project aims to investigate and implement energy‑optimal path planning and CAD‑based trajectory generation for industrial robot manipulators. The student will perform a comprehensive literature review on energy‑efficient robot motion planning, CAD‑to‑path conversion techniques, and industrial trajectory optimization. Based on the findings, the student will implement selected algorithms in the ENCY robot programming environment, supporting automatic extraction of paths from CAD models and optimizing trajectories under energy-related constraints (joint torque, motor models, velocity/acceleration profiles). The generated paths will be tested both in simulation and on a Borunte industrial robot arm. The project contributes to modern manufacturing goals such as sustainability, reduced operational cost, and high‑precision automation.