An Intuitive Framework to Minimize Cognitive Load in Robotic Control: A Comparative Evaluation of Body Parts

Abstract

Within the domain of robotic control frameworks, a critical consideration is the minimization of cognitive load for the operator. Many past studies have aimed to achieve this by incorporating human motion into control systems. However, these methods often relied on motion capture systems, necessitating the cumbersome procedure of wearing equipment and calibrating sensors. This paper introduces an intuitive framework that utilizes raw values from a single Inertial Measurement Unit (IMU) sensor to capture the operator's intent for robot control, thereby eliminating the need for complex sensor configurations and lengthy setup procedures. Furthermore, our study includes a comparative evaluation to determine the most effective body part - wrist, torso, or head - compared to traditional joystick control, in terms of minimizing cognitive load and maximizing intuitiveness. The evaluation criteria include stability, cognitive load, usability, and task completion time, with experiments involving both expert and non-expert users. Our findings indicate that wrist-based control is most beneficial for experts, improving stability, cognitive load management, usability, and completion speed. In contrast, non-experts prefer torso-based control for its intuitive nature, ease of use, and stability. Notably, the wrist and torso controls, which were most favored by the subjects, are assessed as more user-friendly than traditional joystick controls due to their hands-free operation capability. The practicality of our proposed framework is underscored by its potential compatibility with commonly available smart devices, paving the way for future research in realistic application scenarios. © 2024 IEEE.