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Research Papers: Design of Mechanisms and Robotic Systems

Automated Synthesis of Passive Dynamic Brachiating Robots Using a Simulation-Driven Graph Grammar Method

[+] Author and Article Information
Fritz Stöckli

Engineering Design and Computing Laboratory,
Department of Mechanical and
Process Engineering,
ETH Zürich,
Zürich 8092, Switzerland
e-mail: sfritz@ethz.ch

Kristina Shea

Engineering Design and Computing Laboratory,
Department of Mechanical and
Process Engineering,
ETH Zürich,
Zürich 8092, Switzerland
e-mail: kshea@ethz.ch

1Corresponding author.

Contributed by the Mechanisms and Robotics Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received October 28, 2016; final manuscript received June 14, 2017; published online July 24, 2017. Assoc. Editor: Massimiliano Gobbi.

J. Mech. Des 139(9), 092301 (Jul 24, 2017) (9 pages) Paper No: MD-16-1725; doi: 10.1115/1.4037245 History: Received October 28, 2016; Revised June 14, 2017

Passive dynamic systems have the advantage over conventional robotic systems that they do not require actuators and control. Brachiating, in particular, involves the swinging motion of an animal from one branch to the next. Such systems are usually designed manually by human designers and often are bio-inspired. However, a computational design approach has the capability to search vast design spaces and find solutions that go beyond those possible by manual design. This paper addresses the automated design of passive dynamic systems by introducing a graph grammar-based method that integrates dynamic simulation to evaluate and evolve configurations. In particular, the method is shown to find different, new solutions to the problem of the design of two-dimensional passive, dynamic, continuous contact, brachiating robots. The presented graph grammar rules preserve symmetry among robot topologies. A separation of parametric multi-objective optimization and topologic synthesis is proposed, considering four objectives: number of successful swings, deviation from cyclic motion, required space, and number of bodies. The results show that multiple solutions with varying complexity are found that trade-off cyclic motion and the space required. Compared to research on automated design synthesis of actuated and controlled robotic systems, this paper contributes a new method for passive dynamic systems that integrates dynamic simulation.

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Figures

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Fig. 1

Rigid body model of a monkey with five bodies as used in Ref. [6]

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Fig. 2

Three swings of (a) the basic solution: single pendulum and (b) a two-body solution requiring less space than the basic solution

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Fig. 3

Structure of the method

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Fig. 4

Hierarchy of nodes in the metamodel of the graph grammar

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Fig. 5

Simple examples of graph representations of dynamic systems: (a) graph representing a single pendulum, (b) single pendulum, (c) graph representing two-body configuration, and (d) two-body configuration (the legend of Fig. 2 applies here)

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Fig. 6

Symmetric graph example: (a) graph and (b) corresponding multibody system

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Fig. 7

Symmetric graph example extended with bodies of type generic: (a) graph and (b) corresponding multibody system

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Fig. 8

Rule example 1: replacing a body of type center with a body pair of type left/right

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Fig. 9

Rule example 2: adding a body pair of type left/right to an existing body pair of type left/right

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Fig. 11

The number of successful swings of the individuals in the final population of a genetic algorithm for three different topologies and different sets of weight factors

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Fig. 15

System examples with different complexity and good performance in all other criteria

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Fig. 14

System examples with good performance in all criteria except space requirement

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Fig. 13

System examples with mediocre performance in cyclic locomotion

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Fig. 12

Evaluation of a set of solutions of eight different topologies

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Fig. 16

Two-body prototype with ball bearings and electromagnetic gripping

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