Sheet Metal Bending Robot Path Planning With SVSDF Collision Safety

The patent transforms the path planning problem from a single-objective optimization to a multi-objective optimization by changing the parameter representation. It introduces a composite cost function that incorporates both path length and safety distance metrics, allowing the system to simultaneously optimize for efficiency and safety by adjusting the weight parameters in the cost function.

The patent adds a new dimension to the path planning by introducing the safety distance metric as an additional optimization dimension. Instead of only minimizing path length in the traditional configuration space, the system now operates in an extended space that includes safety margins, effectively adding another degree of freedom to the optimization problem.

The patent introduces signed distance fields as an intermediary representation between the discrete sampling and continuous collision detection requirements. The SDF provides a continuous mathematical representation of the environment geometry that can be efficiently queried at any point, serving as a mediator that enables both fast calculation and accurate collision detection without requiring dense discrete sampling.

The patent replaces the traditional mechanical approach of dense discrete sampling with a field-based computational approach. Instead of using numerous discrete samples to approximate continuous space, the system uses continuous distance field representations that can be evaluated at any point, substituting the sampling mechanism with a mathematical field model that provides both efficiency and accuracy.