This article investigates optimal consensus problems of switching multiagent systems (MASs). For such kind of MASs, local neighborhood tracking error (LNTE) system is time varying because of the switching communication graph (CG). Existing performance index defined on the LNTE system is thus invalid for the switching MASs. This article addresses this problem by defining a new augmented LNTE system. The augmented LNTE system is constructed using the joint CG and is thus time-invariant. Subsequently, the optimal consensus problems for the MASs are formulated using the augmented LNTE system. Value iteration algorithm that employs an actor-critic network is used to learn the optimal controller. The article provides a theoretical analysis demonstrating the learning stability and control stability of the value iteration method. Furthermore, we also show that the MASs will reach approximate Nash equilibrium. Simulation results proves the effectiveness of the proposed method.

With aging, human skin develops a dry condition called senile xerosis. The skin lesion can be prevented by daily skin care such as applying an ointment containing moisturizing factors several times a day. Aged persons, however, have difficulties in accessing the back and rely therefore on nursing care for such treatment. Unfortunately, in underpopulated areas such nursing care may not always be available. To tackle this problem, the concept of a skincare robot is proposed. The feasibility of the concept is then confirmed by designing a real skincare robot and by performing experiments for applying ointment on human's back. The robot developed is able to recognize the shape of the body, to plan the appropriate motion paths for the hand, and to execute the task without applying any excessive forces.

This paper addresses the problem of naturally looking and energy efficient walk of biped humanoids. We presuppose that such walk requires motion control capability around kinematic singularities, such that the knee can be fully extended. This problem is tackled by adopting the singularity-consistent method developed for manipulator motion control at and around kinematic singularities. We implemented the method with a HOAP-2 humanoid robot, demonstrating stable static walk as a first step in this direction

We study the behavior control of a robot using orbits of nonlinear dynamics. The behavior generation and control using entrainment and synchronization phenomena in nonlinear dynamical systems is discussed. The behavior of the Arnold equation, which is known to show the chaotic behavior of non-compressive perfect fluid, is analyzed. Methods to integrate the dynamics into the information processing system of a robot is discussed.

In this paper, we develop a method to impart the chaotic nature to a mobile robot. The chaotic mobile robot implies a mobile robot with a controller that ensures chaotic motions. Chaotic motion is characterized by the topological transitivity and the sensitive dependence on initial conditions. Due to the topological transitivity, the chaotic mobile robot is guaranteed to scan the whole connected workspace. For scanning motion, the chaotic robot neither requires the map of the workspace nor plans the global motion. It only requires the measurement of the local normal of the workspace boundary when it comes close to it. We design the controller such that the total dynamics of the mobile robot is represented by the Arnold equation, which is known to show the chaotic behavior of noncompressive perfect fluid. Experimental results and their analysis illustrate the usefulness of the proposed controller.

In this paper, we develop a method to impart the chaotic nature to a mobile robot. The chaotic mobile robot implies a mobile robot with a controller that ensures chaotic motions. Chaotic motion is characterized by the topological transitivity and the sensitive dependence on initial conditions. Due to the topological transitivity, the chaotic mobile robot is guaranteed to scan the whole connected workspace. For scanning motion, the chaotic robot does not require the map of workspace. It only requires to measure the local normal of the workspace boundary when it comes close to it. We design the controller such that the total dynamics of mobile robot is represented by the Arnold equation, which is known to show the chaotic behavior of noncompressive perfect fluid. Experimental results and their analysis illustrate the usefulness of the proposed controller.