STEP: State Estimator for Legged Robots Using a Preintegrated foot Velocity Factor
This work addresses state estimation for legged robots in challenging environments, representing an incremental improvement by eliminating the need for contact detection.
The authors tackled the problem of state estimation for legged robots by proposing STEP, a novel estimator that uses a preintegrated foot velocity factor without the non-slip assumption, validated in simulations and real-world experiments on uneven or slippery terrains.
We propose a novel state estimator for legged robots, STEP, achieved through a novel preintegrated foot velocity factor. In the preintegrated foot velocity factor, the usual non-slip assumption is not adopted. Instead, the end effector velocity becomes observable by exploiting the body speed obtained from a stereo camera. In other words, the preintegrated end effector's pose can be estimated. Another advantage of our approach is that it eliminates the necessity for a contact detection step, unlike the typical approaches. The proposed method has also been validated in harsh-environment simulations and real-world experiments containing uneven or slippery terrains.