Abstract
This paper introduces a new concept of multi-locomotion robot inspired by an animal. The robot, ‘Gorilla Robot II’, can select the appropriate locomotion (from biped locomotion, quadruped locomotion and brachiation) according to an environment or task. We consider ‘brachiation’ to be one of the most dynamic of animal motions. To develop a brachiation controller, architecture of the hierarchical behaviour-based controller, which consists of behaviour controllers and behaviour coordinators, was used. To achieve better brachiation, an enhanced learning method for motion control, adjusting the timing of the behaviour coordination, is proposed. Finally, it is shown that the developed robot successfully performs two types of brachiation and continuous locomotion.
Highlights
Our goal is to realise a robot that can intelligently assist and perform a heavy, boring and time-consuming task in place of a human
The learning algorithm explained above is applied to the control problem of three-dimensional brachiation using Gorilla Robot II
An unsupervised learning algorithm such as reinforcement learning has generally poor ability to find optimal solutions; task decomposition or hierarchical structure are required to obtain a controller for a robot with multiple degrees of freedom
Summary
Our goal is to realise a robot that can intelligently assist and perform a heavy, boring and time-consuming task in place of a human. This useful robot needs to have good hardware (ie sensors, actuators and a processor) and good software (ie human-like intelligence information processing). This motion is the kind of dynamic and dexterous action that apes perform as a lifework (Simons 1972).
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