Symmetries Here and There, Combined Everywhere: Cross-space Symmetry Compositions in Robotics
The paper introduces cross-space symmetry compositions, a method for learning robot policies that are simultaneously equivariant to multiple symmetries across configuration and task spaces. By jointly leveraging these symmetries rather than treating them separately, the framework improves generalization in simulated and real-world experiments.