PROJECT TOPICComputer Vision & Embedded AI
Edge-Processed Gesture Arm
A human-robot interaction concept examining edge neural networks that track 21 hand skeleton keypoints from a standard video stream to teleoperate a robotic arm with intuitive gestures.
Intuitive Non-Contact Teleoperation
- ✓Extracts 21 3D hand coordinates in real time using lightweight edge neural networks.
- ✓Maps spatial wrist orientation directly to robot end-effector coordinates.
- ✓Features deadband filtering and safety limits to prevent sudden erratic jerks.
The Engineering Challenge
Problem / Objective
Teaching pendants and joysticks have steep learning curves and disconnect operators from natural spatial movements during teleoperation.
Conceptual Signal Flow
System Concept
Monocular Camera → Hand Keypoint Neural Inference → Vector Mapping → Robot Arm Joint Controllers.
Architecture Modules
1Monocular Video Input Stage
2Edge Hand Keypoint Estimator
3Kinematic Mapping & Smoothing Engine
4Articulated Robot Joint Interface
Hardware Categories
USB CameraEdge Neural Compute Stick/BoardArticulated Robotic ArmSafety Enable Pedal
Technologies & Software
Hand TrackingComputer VisionEdge AIRobot TeleoperationMediaPipe / Lightweight Pose ModelsRobot Inverse Kinematics Driver
Engineering Considerations & Edge Cases
- Optical occlusion when hand turns sideways to the camera
- Latent lag causing operator over-correction
Applications
Hazardous lab material manipulation
Intuitive welding arm teaching
Assistive robotics interfaces
Engineering Inquiry & Collaboration
Interested in Developing this Architecture?
Connect directly with Tamizh Tech engineers in Coimbatore to discuss mechanical fabrication, sensor selection, firmware implementation, or turnkey system commissioning.