NSPG: An Efficient Posture Generator Based on Null-Space Alteration and Kinetostatics Constraints - Rossini, Luca; Hoffman, Enrico Mingo; Laurenzi, Arturo; Tsagarakis, Nikos G. (Frontiers in Robotics and AI, 2021)
Most of the locomotion and contact planners for multi-limbed robots rely on a reduction of the search space to improve the performance of their algorithm. Posture generation plays a fundamental role in these types of planners providing a collision-free, statically stable whole-body posture, projected onto the planned contacts. However, posture generation becomes particularly tedious for complex robots moving in cluttered environments, in which feasibility can be hard to accomplish. In this work, we take advantage of the kinematic structure of a multi-limbed robot to present a posture generator based on hierarchical inverse kinematics and contact force optimization, called Null-Space Posture Generator (NSPG), able to efficiently satisfy the aforementioned requisites in short times. A new configuration of the robot is produced through conservatively altering a given nominal posture exploiting the null-space of the contacts manifold, satisfying geometrical and kineto-statics constraints. This is achieved through an adaptive random velocity vector generator that lets the robot explore its work-space. To prove the generality of the proposed approach, the NSPG is verified in complex scenarios that both the hybrid-wheeled legged quadrupedal robot CENTAURO and the bipedal humanoid robot COMAN+ has to traverse.