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Enhancing Robot Interaction through Military Gesture Recognition

This project explores the development of a gesture recognition interface that allows robots to interpret and act upon natural human gestures, especially in scenarios where speech is ineffective. By utilizing the Xbox Kinect, the interface processes skeleton data to classify gestures using a C4.5 decision tree approach. Key gestures like "Freeze," "Stop," and "Cover" are analyzed and implemented, ensuring no special training is required. Future work includes refining gesture classification and improving response accuracy, paving the way for seamless human-robot interactions.

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Enhancing Robot Interaction through Military Gesture Recognition

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Presentation Transcript

  1. Senior Project – Computer Science – 2013Recognizing military Gesturesdeveloping a Gesture Recognition interface By: Jonathan Lebron Advisor: Nick Webb

  2. Motivation • Scenarios where speech would not be possible or optimal solution • Giving natural gestures to Robots that resemble Human-to-Human interaction • No need for special training • Incorporating both speech an gesture would be ideal, but this problem is out of scope

  3. Research Question • How do you give a robot a sequence of natural gestures to interpret and act upon? Xbox Kinect

  4. How It Works • Perform Gesture • Kinect reads skeleton data • Data gets transformed into angles • Classifier reads angles and determines gesture using C4.5 decision tree left_shoulder: 0.35, 0.12, 2.19 left_elbow: -0.18, -0.10, 2.02 left_hand: -0.13, -0.34, 1.924

  5. Classification Gestures Abreast Enemy Freeze Stop Listen Rifle Cover Classifier Angles handTheta handPhi elbowTheta elbowPhi

  6. Classification • How do we handle erroneous data? • When do we know when to execute the sequence? • What actions can we expect from the robot?

  7. Software Design

  8. Adding Gestures • Create new gestures • Replace old gestures • Combining gestures

  9. Conclusion • Future Work • Wrap-up • Q&A

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