ICRA'09 Paper Abstract


Paper FrC1.5

Arslan, Omur (Bilkent University), Saranli, Uluc (Bilkent University), Morgul, Omer (Bilkent University)

An Approximate Stance Map of the Spring Mass Hopper with Gravity Correction for Nonsymmetric Locomotions

Scheduled for presentation during the Regular Sessions "Legged Robots and Humanoid Locomotion - III" (FrC1), Friday, May 15, 2009, 14:50−15:10, MainHall

2009 IEEE International Conference on Robotics and Automation, May 12 - 17, 2009, Kobe, Japan

This information is tentative and subject to change. Compiled on January 21, 2022

Keywords Legged Robots and Humanoid Locomotion, Motion and Path Planning, Discrete Event Dynamic Systems


The Spring-Loaded Inverted Pendulum (SLIP) model has long been established as an effective and accurate descriptive model for running animals of widely differing sizes and morphologies. Not surprisingly, the ability of such a simple spring-mass model to capture the essence of running motivated several hopping robot designs as well as the use of the SLIP model as a control target for more complex legged robot morphologies. Further research on the SLIP model led to the discovery of several analytic approximations to its normally nonintegrable dynamics. However, these approximations mostly focus on steady-state running with symmetric trajectories due to their linearization of gravitational effects, an assumption that is quickly violated for locomotion on more complex terrain wherein transient, non-symmetric trajectories dominate. In this paper, we introduce a novel gravity correction scheme that extends on one of the more recent analytic approximations to the SLIP dynamics and achieves good accuracy even for highly non-symmetric trajectories. Our approach is based on incorporating the total effect of gravity on the angular momentum throughout a single stance phase and allows us to preserve the analytic simplicity of the approximation to support our longer term research on reactive footstep planning for dynamic legged locomotion. We compare the performance of our method in simulation to two other existing analytic approximations and show that it mostly outperforms them.



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