Learning basic navigation for personal satellite assistant using neuroevolution

ABSTRACT

The Personal Satellite Assistant (PSA) is a small robot proposed by NASA to assist astronauts who are living and working aboard the space shuttle or space station. To help the astronaut, it has to move around safely. Navigation is made difficult by the arrangement of thrusters. Only forward and leftward thrust is available and rotation will introduce translation. This paper shows how stable navigation can be achieved through neuroevolution in three basic navigation tasks: (1) Stopping autorotation, (2) Turning 90 degrees, and (3) Moving forward to a position. The results show that it is possible to learn to control the PSA stably and efficiently through neuroevolution.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
      I.2.9 Robotics

General Terms:
Algorithms, Experimentation, Performance

Keywords:
PSA, enforced sub-populations, neuroevolution