LRF Assisted Autonomous Walking in Rough Terrain for Hexapod Robot COMET-IV

Chapter
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 65)

Abstract

This paper presents an autonomous navigation system for a hydraulically driven hexapod robot COMET-IV. This work aims to improve the capabilities and increase autonomy of the robot by improving mapping technique for unknown environment, obstacle avoidances, and leg motion control assistance using a laser range finder (LRF) 3D point clouds data. In the previous research, the Grid-based Walking Trajectory for Legged Robot (GWTLR) algorithm, in which the A* algorithm and Growing Obstacle methods are referenced, was developed (Molfino et al. J Ind Rob 2:163–170, 2005) and successfully applied to the COMET-IV, for avoiding obstacles. In this work, the capabilities of the legged robot to cross over, step on, ascending and descending a cliff are capitalized by reconditioning leg swing trajectory based on obstacles geometric. Experimental results of the proposed methods show that the trajectory planning can be done autonomously under the unknown environment. Therefore, the proposed methods were proven to be highly potential to be applied as a part of the overall system for actual stochastic terrain navigation.

Keywords

Cross-over obstacles Leg swing trajectory Obstacle avoidance Step-on obstacle 

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Copyright information

© Springer Japan 2013

Authors and Affiliations

  1. 1.Universiti Malaysia PahangKuantanMalaysia
  2. 2.Artificial System Science, Graduate School of EngineeringChiba UniversityChibaJapan

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