Humanoid robots have been considered ideal for automating daily tasks, though most research has centered on bipedal locomotion. Many activities we do routinely, such as driving a car, require real-time system manipulation as well as substantial field-specific knowledge. Recent breakthroughs in natural language processing, particularly with large language models (LLMs), are empowering humanoid robots to access and process vast information sources and operate systems with an unprecedented level of autonomy. This article introduces PIBOT, a humanoid robot that can pilot unmodified general aviation (GA) aircraft, physically manipulating instruments while following strict rules of the air and verbally communicating with copilots and air traffic controllers (ATCs). Building on these capabilities, we developed an LLM-based task planner that interprets natural language commands, translating them into action sequences. Then, the behavior decision module breaks tasks into precise limb movements, enabling humanlike control of cockpit instruments. In a series of rigorous simulations, PIBOT demonstrates its capabilities to successfully take off and land an airplane from a cold-and-dark start, showcasing its potential for a fully autonomous robot pilot.
