Research Papers

Analysis and Optimization of One-Degree of Freedom Robotic Legs

[+] Author and Article Information
Lionel Birglen

Robotics Laboratory,
Department of Mechanical Engineering,
Polytechnique Montreal,
Montreal, QC H3C 3A7, Canada
e-mail: lionel.birglen@polymtl.ca

Carlos Ruella

Robotics Laboratory,
Department of Mechanical Engineering,
Polytechnique Montreal,
Montreal, QC H3C 3A7, Canada
e-mail: carlos.ruella@polymtl.ca

1Corresponding author.

Contributed by the Mechanisms and Robotics Committee of ASME for publication in the JOURNAL OF MECHANISMS AND ROBOTICS. Manuscript received May 13, 2013; final manuscript received February 17, 2014; published online June 5, 2014. Assoc. Editor: Philippe Wenger.

J. Mechanisms Robotics 6(4), 041004 (Jun 05, 2014) (8 pages) Paper No: JMR-13-1094; doi: 10.1115/1.4027234 History: Received May 13, 2013; Revised February 17, 2014

Almost all walking robots are composed of two or more multi-degrees-of-freedom (DOFs) legs which give them a good ability to traverse obstacles. Nevertheless, their speed and efficiency when traversing rough terrains is, in most cases, arguably limited. Additionally, they have the disadvantage of a generally lower reliability. The design of robust and efficient 1-DOF leg is, on the other hand, a complex process. In this paper, a method to analyze and optimize 1-DOF robotic legs is proposed. The results of a virtual simulation are used in combination with some performance indices to optimize the geometric parameters of 1-DOF legs. Finally, the results of the simulation and the actual walking performance of a prototype using four legs with the computed optimal parameters are presented and compared with the simulator results. The validation of the simulation model and the optimization method proposed in this paper represents the main contribution of this work.

Copyright © 2014 by ASME
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Fig. 4

Example of the trajectory and forces of the foot of a 1-DOF leg

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Fig. 3

Flowchart of the proposed algorithm

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Fig. 2

Sample of three generated synthetic terrain from the same real terrain profile

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Fig. 1

Digital picture of an uneven terrain profile

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Fig. 10

Snapshots of the robot traversing the uneven terrain

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Fig. 6

Trajectories of the Chebyshev leg with optimal geometric parameters

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Fig. 8

Simulated foot trajectories over different terrains

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Fig. 9

Error between simulation and experimentation over different terrains




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