Laercio R. Filho

Deep Neural Networks for Inverse Kinematics With Multi-Valued Solution Spaces: Limitations and Hybrid Learning––Optimization Approach

The results indicate that inverse kinematics problems characterized by one-to-many mappings cannot be effectively treated as deterministic regression tasks and demonstrate that informed neural initialization combined with numerical optimization constitutes an effective and computationally efficient solution strategy.