Intuitive Control of a Robotic Arm via Inertial Sensor Fusion and EMG for Assistive Applications

We present an intuitive, real-time control systemfor a 6-axis robotic arm, designed to support assistive applications in biomedical contexts. Using four MARG-based inertial sensors placed on the arm and hand, human motion is captured and mapped to robot kinematics via quaternion-based sensor fusion and a two-step calibration process. The resulting end-effector pose is scaled to match the robot's workspace, while EMG signals enable control of a robotic gripper through thumb-index gripping gestures. The system enables direct, gesture-based control without extensive training, making it accessible for users with limited mobility but preserved upper limb function. Evaluation results confirm stable, low-latency operation during pick-and-place tasks, with users intuitively compensating for minor sensor inaccuracies through visual feedback. This approach demonstrates strong potential for assistive robotics in home or care environments, particularly where conventional control methods are unsuitable.