Voice-Controlled UFactory xArm 850

This project enables hands-free operation of industrial robotic arms through natural language voice commands. By implementing speech recognition and natural language understanding, the system makes robotics more accessible and allows operators to multitask while controlling robotic systems.

The voice interface demonstrates how intuitive human-robot interaction can improve workflow efficiency in industrial and research settings.

The system uses Python's SpeechRecognition library with Google Speech Recognition API for audio-to-text conversion. The natural language processing pipeline parses voice commands using pattern matching and keyword extraction to identify robot actions (move, pick, place) and parameters (positions, objects).

The UFactory SDK provides low-level robot control interfacing with the xArm 850. The system maintains a state machine tracking current robot position and operation mode. Command validation ensures safety by checking workspace limits and collision possibilities before executing movements.

Predefined position labels allow users to reference locations by name ("home position", "pickup zone") rather than coordinates. The system includes voice feedback confirming command interpretation before execution.

Successfully demonstrated voice control for common pick-and-place operations with 90%+ command recognition accuracy in quiet environments. Response latency from voice command to robot movement initiation averages 1.5 seconds. The natural language interface reduced training time for new operators by 40% compared to traditional pendant programming.

Future improvements include custom wake word activation, noise-robust recognition, and multi-robot coordination through voice commands.