Artificial Endocrine Controller for Power Management in Robotic Systems

Colin Sauze, Mark Neal

Research output: Contribution to journalArticlepeer-review

22 Citations (SciVal)


The robots that operate autonomously for extended periods in remote environments are often limited to gather only small amounts of power through photovoltaic solar panels. Such limited power budgets make power management critical to the success of the robot's mission. Artificial endocrine controllers, inspired by the mammalian endocrine system, have shown potential as a method for managing competing demands, gradually switching between behaviors, synchronizing behavior with external events, and maintaining a stable internal state of the robot. This paper reports the results obtained using these methods to manage power in an autonomous sailing robot. Artificial neural networks are used for sail and rudder control, while an artificial endocrine controller modulates the magnitude of actuator movements in response to battery or sunlight levels. Experiments are performed both in simulation and using a real robot. In simulation a 13-fold reduction in median power consumption is achieved; in the robot this is reduced to a twofold reduction because of the limitations of the simulation model. Additional simulations of a long term mission demonstrate the controller's ability to make gradual behavioral transitions and to synchronize behaviors with diurnal and seasonal changes in sunlight levels.
Original languageEnglish
Pages (from-to)1973-1985
Number of pages1
JournalIEEE Transactions on Neural Networks and Learning Systems
Issue number12
Early online date09 Jul 2013
Publication statusPublished - Dec 2013


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