Traditional industries face barriers to adopting robotic arms due to skill gaps and psychological concerns among workers. This work introduces a constraint-adaptive shared autonomy system to address these challenges. The system simplifies teleoperation using geometric constraints and error-tolerant design, enabling precise control while reducing user workload. The CNC machine cleaning task, developed from the daily routine work of a local Public Transport Company in Hong Kong, guides workers into the field of Robotics. Applied to the proposed task this solution enhances efficiency, safety, and inclusivity. This work provides “equitable quality education” and “lifelong learning” for people, as well as “fosters innovation” in traditional industries.