Semiosis of Autonomous Mobile Robots

The stability of motion in multi-dimensional dynamical systems represents a mechanism in which their behaviors are compressed into low dimensional dynamics through interaction among their constituent elements. In autonomous mobile mechanical system design, the degree of freedom is compressed in the manner that even involves a degree of freedom of the environment in addition to that intrinsic to the robot, which creates qualitative stability (isomorphism) of motion patterns. At the same time, by generating versatility within, adaptation to the environment is created. Alternate repetition of the order-structure- formation phase and collapse phase underlies the adaptation of an autonomous mobile mechanical system, which we consider to represent a complex system.
The group of Tsuchiya (Doshisha University) and Aoi (Kyoto University) carries out research on the control and design theory of quadrupedal and bipedal robots, taking self-organization and phase transition by control parameters as the principle of motion control. In this research, the nervous system, which is capable of generating voluntary activity patterns related to locomotion, draws in and strongly couples the actions while interacting with a body that is in physical contact with the environment. This results in a mechanism that can generate versatile and adaptive walking motions. The group investigates into how these walking patterns are acquired internally within the walking actors (i.e., design of signs) as well as how the gait transition is attained taking account of kinematic coordination between these gait patterns (i.e., performance of signs).
The group of Yokokoji (Kyoto University) deals with a robot’s function of the ability to receive task instructions from a human. The task is conducted through the bodily interactions between the robots and the humans, while each of those have different physical bodies and encounter the difficulties in sharing the meanings of the instructed task with each other. The group has already succeeded in developing a robot hand that can fold an origami work “Tadpole”. Analyzing the instructed series of actions provided by the human and segmenting these into a series of significant chunks, this group first elucidates the human instructor’s recognition of the task structure of folding an origami work (i.e., design of signs). Then, it will be investigated how the robot interprets this instruction and internalizes this so that it can be used for its behavior generation (i.e., performance of signs).

The group of Nakanishi and Sawaragi (Kyoto University) focuses on the robot’s ability of perceiving the environment with uncertainties through the interaction, and of changing and selecting its behavior adaptively. This group uses autonomous robots such as an unmanned helicopter and a rover and to explore control system design using a neural network as an adaptive component. By combining off-line learning on a simulator and on-line learning in the actual environment, this group demonstrates robust adaptation to the problems encountered by actual machines such as model learning errors, changes in environment. As a control method with versatility, this group investigates into multiple modules that are acquired by the robots within those and how these enable the robot to adapt to environmental changes. The issues on how these individual modules selectively learn and what aspects of the environment these modules signify are of importance (i.e., design of signs), and are discussed in terms of semiosis.