Masayuki Fujita

Shunya Yamashita, Takeshi Hatanaka, Junya Yamauchi et al.

In this paper, we revisit primal-dual dynamics for convex optimization and present a generalization of the dynamics based on the concept of passivity. It is then proved that supplying a stable zero to one of the integrators in the dynamics allows one to eliminate the assumption of strict convexity on the cost function based on the passivity paradigm together with the invariance principle for Caratheodory systems. We then show that the present algorithm is also a generalization of existing augmented Lagrangian-based primal-dual dynamics, and discuss the benefit of the present generalization in terms of noise reduction and convergence speed.

Tatsuhiko Goto, Takeshi Hatanaka, Masayuki Fujita

This paper handles a kind of strategic game called potential games and develops a novel learning algorithm Payoff-based Inhomogeneous Partially Irrational Play (PIPIP). The present algorithm is based on Distributed Inhomogeneous Synchronous Learning (DISL) presented in an existing work but, unlike DISL,PIPIP allows agents to make irrational decisions with a specified probability, i.e. agents can choose an action with a low utility from the past actions stored in the memory. Due to the irrational decisions, we can prove convergence in probability of collective actions to potential function maximizers. Finally, we demonstrate the effectiveness of the present algorithm through experiments on a sensor coverage problem. It is revealed through the demonstration that the present learning algorithm successfully leads agents to around potential function maximizers even in the presence of undesirable Nash equilibria. We also see through the experiment with a moving density function that PIPIP has adaptability to environmental changes.

Takeshi Hatanaka, Masayuki Fujita

This paper investigates cooperative estimation of 3D target object motion for visual sensor networks. In particular, we consider the situation where multiple smart vision cameras see a group of target objects. The objective here is to meet two requirements simultaneously: averaging for static objects and tracking to moving target objects. For this purpose, we present a cooperative estimation mechanism called networked visual motion observer. We then derive an upper bound of the ultimate error between the actual average and the estimates produced by the present networked estimation mechanism. Moreover, we also analyze the tracking performance of the estimates to moving target objects. Finally the effectiveness of the networked visual motion observer is demonstrated through simulation.

Takeshi Hatanaka, Yasuaki Wasa, Masayuki Fujita

This paper investigates cooperative environmental monitoring for Pan-Tilt-Zoom (PTZ) visual sensor networks. We first present a novel formulation of the optimal environmental monitoring problem, whose objective function is intertwined with the uncertain state of the environment. In addition, due to the large volume of vision data, it is desired for each sensor to execute processing through local computation and communication. To address the issues, we present a distributed solution to the problem based on game theoretic cooperative control and payoff-based learning. At the first stage, a utility function is designed so that the resulting game constitutes a potential game with potential function equal to the group objective function, where the designed utility is shown to be computable through local image processing and communication. Then, we present a payoff-based learning algorithm so that the sensors are led to the global objective function maximizers without using any prior information on the environmental state. Finally, we run experiments to demonstrate the effectiveness of the present approach.

Li Yi, Shota Ito, Chao Tang et al.

Resonant tunneling diodes (RTDs) support room-temperature terahertz (THz) oscillation and simultaneous THz-band detection, enabling compact monostatic THz sensors for practical and cost-effective sensing applications. In this paper, we present a highly integrated 280 GHz-band radar system based on a single RTD that exploits the self-mixing effect to generate a low-frequency interferometric signal. The resulting self-mixing signal is further analyzed from a radar perspective and processed to extract micrometer-scale displacement and thin-film thickness variations. Experimentally, the proposed system demonstrates a minimum detectable displacement of approximately 5 um and quantitatively resolves polymer film thicknesses of 12.5, 25, and 50 um.

Takeshi Hatanaka, Takayuki Nishi, Masayuki Fujita

This paper investigates vision-based cooperative estimation of a 3D target object pose for visual sensor networks. In our previous works, we presented an estimation mechanism called networked visual motion observer achieving averaging of local pose estimates in real time. This paper extends the mechanism so that it works even in the presence of cameras not viewing the target due to the limited view angles and obstructions in order to fully take advantage of the networked vision system. Then, we analyze the averaging performance attained by the proposed mechanism and clarify a relation between the feedback gains in the algorithm and the performance. Finally, we demonstrate the effectiveness of the algorithm through simulation.

Tam Nguyen, Takeshi Hatanaka, Mamoru Doi et al.

This paper focuses on a passivity-based distributed reference governor (RG) applied to a pre-stabilized mobile robotic network. The novelty of this paper lies in the method used to solve the RG problem, where a passivity-based distributed optimization scheme is proposed. In particular, the gradient descent method minimizes the global objective function while the dual ascent method maximizes the Hamiltonian. To make the agents converge to the agreed optimal solution, a proportional-integral consensus estimator is used. This paper proves the convergence of the state estimates of the RG to the optimal solution through passivity arguments, considering the physical system static. Then, the effectiveness of the scheme considering the dynamics of the physical system is demonstrated through simulations and experiments.