Robust human-inspired power law trajectories for humanoid HRP-2 robot - LAAS - Laboratoire d'Analyse et d'Architecture des Systèmes Access content directly
Conference Papers Year : 2016

Robust human-inspired power law trajectories for humanoid HRP-2 robot


The one-third power law models how human speed of motion depends on the path's curvature. This paper studies the interest of using this law for humanoid robot walking control along a planar reference trajectory. We predicted that humanoid robots following a reference trajectory may benefit from one-third power law speed profiles by reducing closed-loop drift and energy consumption. To robustly execute reference trajectories, we use contracting morphed Andronov-Hopf oscillators, regularized to follow a power law while converging to a planned cyclic trajectory. The walking pattern generator of HRP-2 uses these guiding dynamics to walk along elliptic trajectories. In dynamic simulation, we observe minimal geometric drift with the one-third power law, demonstrating increased precision compared with constant speed and other power laws. Closed-loop experiments on HRP-2 result in a small drift of all power law motions from the reference trajectory, showing the efficiency of the control architecture. We observe that the one-third power law controller demands less compensatory action, and therefore lowers the burden on the hardware. Slowing in curved movement regions also unexpectedly allows for faster overall movement.
Fichier principal
Vignette du fichier
Karklinsky-et-al-2016.pdf (1.37 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02002597 , version 1 (31-01-2019)



M Karklinsky, Maximilien Naveau, A Mukovskiy, Olivier Stasse, T Flash, et al.. Robust human-inspired power law trajectories for humanoid HRP-2 robot. IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob), IEEE, Jun 2016, Singapour, Singapore. 8p., ⟨10.1109/BIOROB.2016.7523606⟩. ⟨hal-02002597⟩
48 View
8 Download



Gmail Facebook X LinkedIn More