Unknown Rough Terrain Research Articles

PDAC-Based 3-D Biped Walking Adapted to Rough Terrain Environment

This paper deals with the 3-D biped walking of a humanoid type robot over rough terrain. We previously proposed efficient 3-D biped walking control using Passive Dynamic Autonomous Control (PDAC) based on the assumption of point-contact and virtual holonomic constraint of robot joints. Walking adaptability has not, however, been analyzed. We thus analyze the environmental adaptability of PDAC-based walking method in this paper. The robot is modeled as a variable-length 3-D inverted pendulum whose dynamics is modeled as a 2-D autonomous system by applying PDAC. We analyze the stability of the 2-D autonomous system using a Poincaré map and derive the stable range of uneven height over rough terrain. We then experimentally validate 3-D biped walking on unknown rough terrain using our humanoid type robot, Gorilla Robot III.

Running over unknown rough terrain with a one-legged planar robot

The ability to traverse unknown, rough terrain is an advantage that legged locomoters have over their wheeled counterparts. However, due to the complexity of multi-legged systems, research in legged robotics has not yet been able to reproduce the agility found in the animal kingdom. In an effort to reduce the complexity of the problem, researchers have developed single-legged models to gain insight into the fundamental dynamics of legged running. Inspired by studies of animal locomotion, researchers have proposed numerous control strategies to achieve stable, one-legged running over unknown, rough terrain. One such control strategy incorporates energy variations into the system during the stance phase by changing the force-free leg length as a sinusoidal function of time. In this research, a one-legged planar robot capable of implementing this and other state-of-the-art control strategies was designed and built. Both simulated and experimental results were used to determine and compare the stability of the proposed controllers as the robot was subjected to unknown drop and raised step perturbations equal to 25% of the nominal leg length. This study illustrates the relative advantages of utilizing a minimal-sensing, active energy removal control scheme to stabilize running over rough terrain.

Compliant Terrain Adaptation for Biped Humanoids Without Measuring Ground Surface and Contact Forces

This paper reports the applicability of our passivity-based contact force control framework for biped humanoids. We experimentally demonstrate its adaptation to unknown rough terrain. Adaptation to uneven ground is achieved by optimally distributed antigravitational forces applied to preset contact points in a feedforward manner, even without explicitly measuring the external forces or the terrain shape. Adaptation to unknown inclination is also possible by combining an active balancing controller based on the center-of-mass (CoM) measurements with respect to the inertial frame. Furthermore, we show that a simple impedance controller for supporting the feet or hands allows the robot to adapt to low-friction ground without prior knowledge of the ground friction. This presentation includes supplementary experimental videos that show a full-sized biped humanoid robot balancing on uneven ground or time-varying inclination.