Mobile Robot’s Sensorimotor Developmental Learning From Orientation and Curiosity

Abstract

Simulating biological intelligence has been proved to be an effective way to design intelligent robots, and simultaneously can solve the problems existing in machine learning methods. For creatures, their motor skills achieving is the first stage of learning. By combining two important cognitive elements: orientation and curiosity, this paper proposes a new neurobiologically-inspired sensorimotor developmental learning method for the mobile robot. In this method, curiosity promotes robot's exploration of the environment, while orientation enhances robot's exploitation knowledge of the environment. The orientation cognitive algorithm is designed based on Skinner's operant conditioning theory, and its rationality is proved. The balance of exploration and exploitation, which is a key problem for all the cognitive learning method, is solved in this method. The developmental learning process can avoid fixed sensorimotor mapping space problem, and help reduce learning waste as well as computing waste. All of the developmental learning method's characters are finally verified via simulations on a virtual mobile robot.

Adaptive dynamic windowing approach based on risk degree function

“…At the same time, with the development of computer and control technology, the application field of mobile robot is more and more extensive, and its working environment has changed from the simple indoor structured environment to the unknown unstructured environment in the field (Gyarmati et al, 2021; Zhang et al, 2020). Therefore, how to effectively avoid static or dynamic obstacles and plan the optimal path from the starting point to the target point has become a research focus at present when the surrounding environment is partially known or completely unknown (Wang et al, 2021).…”

Autonomous robot navigation based on a hierarchical cognitive model

“…Moreover, Touretzky et al have further developed the computational model of Skinner's OCR theory [18]. Later, many scholars have carried out extensive research on the computational model of operational conditioned reflexes [19][20][21][22][23][24][25][26][27][28][29][30][31][32]. Robots are showing more self-learning ability and self-adaptability, similar to organisms.…”