• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.7-10
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• 2007

This paper presents a fuzzy footstep planner for humanoid robots in complex environments. First, we define locomotion primitives for humanoid robots. A global planner finds a global path from a navigation map that is generated based on a combination of 2.5 dimensional maps of the 3D workspace. A local planner searches for an optimal sequence of locomotion primitives along the global path by using fuzzy footstep planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.4
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• pp.441-447
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• 2015

This paper proposes a novel fuzzy-based multi-criteria decision making method and implements a footstep planner for humanoid robots with it. Humanoid robots require additional footstep planning process in addition to path planning for the autonomous navigation. Moreover, it is necessary to consider safety and energy consumption as well as path efficiency and multi-criteria decision making is indispensable. The proposed method can provide not only well- distributed and non-dominated, but also more preferable solutions for users. The planned footsteps by the proposed method were verified through simulation. The results indicate that the user's preference is properly reflected in optimized solutions maintaining solution quality.