Human-like approach to footstep planning among obstacles for humanoid robots

Yasar Ayaz, Khalid Munawar, M. Bilal Malik, Atsushi Konno, Masaru Uchiyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)

Abstract

Unlike wheeled robots, humanoid robots are able to overcome obstacles in the environment by stepping over or upon them. Conventional 2D methods for robot navigation fail to exploit this unique ability of humanoids and thus design trajectories only by circumventing obstacles. Recently, globalized algorithms have been presented that take into account this feature of humanoids. However, due to high computational complexity, most of them are very time consuming. In this paper we present a new approach to footstep planning in obstacle cluttered environments that employs a human-like strategy to terrain traversal. Simulation results of its implementation on a model of Saika-3 humanoid robot are also presented. The algorithm, being one of reactive nature, refutes previous claims that reactive algorithms fail to find successful paths in complex obstacle cluttered environments.

Original languageEnglish
Title of host publication2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006
Pages5490-5495
Number of pages6
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006 - Beijing, China
Duration: 2006 Oct 92006 Oct 15

Publication series

NameIEEE International Conference on Intelligent Robots and Systems

Other

Other2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2006
Country/TerritoryChina
CityBeijing
Period06/10/906/10/15

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Human-like approach to footstep planning among obstacles for humanoid robots'. Together they form a unique fingerprint.

Cite this