Adding positional encoding to MLP inputs for robot self-collision detection improves accuracy by capturing high-frequency position variations better than standard inputs.
Fast kinodynamic planning on the constraint manifold with deep neural networks.IEEE Transactions on Robotics, 40:277–297, 2024
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Improving Machine Learning-Based Robot Self-Collision Checking with Input Positional Encoding
Adding positional encoding to MLP inputs for robot self-collision detection improves accuracy by capturing high-frequency position variations better than standard inputs.