The research on intelligent robots will produce robots that are able to operate in everyday life environments, to adapt their program according to environment changes, and to cooperate with other team members and humans. Operating in human environments, robots need to process, in real time, a large amount of sensory data—such as vision, laser, microphone—in order to determine the best action. Intelligent algorithms have been successfully applied to link complex sensory data to robot action. This editorial briefly summarizes recent findings in the field of intelligent robots as described in the articles published in this special issue.
References
[1]
Kuyucu, T.; Tanev, I.; Shimohara, K. Hormone-inspired behaviour switching for the control of collective robotic organisms. Robotics 2013, 2, 165–184, doi:10.3390/robotics2030165.
[2]
Kuremoto, T.; Tsurusaki, T.; Kobayashi, K.; Mabu, S.; Obayashi, M. An improved reinforcement learning system using affective factors. Robotics 2013, 2, 149–164, doi:10.3390/robotics2030149.
[3]
Kormushev, P.; Calinon, S.; Caldwell, D.G. Reinforcement learning in robotics: Applications and real-world challenges. Robotics 2013, 2, 122–148, doi:10.3390/robotics2030122.
[4]
Chaoui, H.; Gueaieb, W.; Biglarbegian, M.; Yagoub, M.C.E. Computationally efficient adaptive type-2 fuzzy control of flexible-joint manipulators. Robotics 2013, 2, 66–91, doi:10.3390/robotics2020066.
[5]
Mano, M.; Capi, G.; Tanaka, N.; Kawahara, S. An artificial neural network based robot controller that uses rat’s brain signals. Robotics 2013, 2, 54–65, doi:10.3390/robotics2020054.
