TY - CONF
T1 - Co-evolving controller and sensing abilities in a simulated Mars Rover explorer
T2 - Evolutionary Computation, 2009. CEC '09. IEEE Congress on
AU - Peniak, M.
AU - Marocco, D.
AU - Cangelosi, A.
N1 - The paper presents an evolutionary robotics model of the Rover Mars robot. This work has the objective to investigate the possibility of using an alternative sensor system, based on infrared sensors, for future rovers capable of performing autonomous tasks in challenging planetary terrain environments. The simulation model of the robot and of Mars terrain is based on a physics engine. The robot control system consists of an artificial neural network trained using evolutionary computation techniques. An adaptive threshold on the infrared sensors has been evolved together with the neural control system to allow the robot to adapt itself to many different environmental conditions. The properties of the behavior obtained after the evolutionary process has been tested by measuring the generalization performance of the rover under various terrain conditions and especially under rough terrain conditions. In addition, the dynamics of the co-evolution between the controller and the threshold has been analyzed. Those analyses show that different pathways have been explored by the evolutionary process in order to adapt the sensing abilities and the control system.
PY - 2009
Y1 - 2009
N2 - The paper presents an evolutionary robotics model of the Rover Mars robot. This work has the objective to investigate the possibility of using an alternative sensor system, based on infrared sensors, for future rovers capable of performing autonomous tasks in challenging planetary terrain environments. The simulation model of the robot and of Mars terrain is based on a physics engine. The robot control system consists of an artificial neural network trained using evolutionary computation techniques. An adaptive threshold on the infrared sensors has been evolved together with the neural control system to allow the robot to adapt itself to many different environmental conditions. The properties of the behavior obtained after the evolutionary process has been tested by measuring the generalization performance of the rover under various terrain conditions and especially under rough terrain conditions. In addition, the dynamics of the co-evolution between the controller and the threshold has been analyzed. Those analyses show that different pathways have been explored by the evolutionary process in order to adapt the sensing abilities and the control system.
AB - The paper presents an evolutionary robotics model of the Rover Mars robot. This work has the objective to investigate the possibility of using an alternative sensor system, based on infrared sensors, for future rovers capable of performing autonomous tasks in challenging planetary terrain environments. The simulation model of the robot and of Mars terrain is based on a physics engine. The robot control system consists of an artificial neural network trained using evolutionary computation techniques. An adaptive threshold on the infrared sensors has been evolved together with the neural control system to allow the robot to adapt itself to many different environmental conditions. The properties of the behavior obtained after the evolutionary process has been tested by measuring the generalization performance of the rover under various terrain conditions and especially under rough terrain conditions. In addition, the dynamics of the co-evolution between the controller and the threshold has been analyzed. Those analyses show that different pathways have been explored by the evolutionary process in order to adapt the sensing abilities and the control system.
KW - Mars
KW - aerospace robotics
KW - evolutionary computation
KW - infrared detectors
KW - learning systems
KW - mobile robots
KW - neurocontrollers
KW - planetary rovers
KW - robot dynamics
KW - adaptive threshold
KW - artificial neural network training
KW - co-evolving controller dynamics
KW - evolutionary computation technique
KW - evolutionary robotics model
KW - infrared sensor system
KW - neural control system
KW - physics engine
KW - planetary terrain environment
KW - robot control system
KW - simulated Mars Rover explorer robot
UR - https://www.scopus.com/pages/publications/70450014834
M3 - Paper
SP - 2772
EP - 2779
ER -