This paper proposes a distributed coverage control strategy for quadcopters equipped with downward-facing cameras that prevents the appearance of unmonitored areas in between the quadcopters' fields of view (FOVs). We derive a necessary and sufficient condition for eliminating any unsurveilled area that may arise in between the FOVs among a trio of quadcopters by utilizing a power diagram, i.e. a weighted Voronoi diagram defined by radii of FOVs. Because this condition can be described as logically combined constraints, we leverage nonsmooth control barrier functions (NCBFs) to prevent the appearance of unmonitored areas among a team's FOV. We then investigate the symmetric properties of the proposed NCBFs to develop a distributed algorithm. The proposed algorithm can support the switching of the NCBFs caused by changes of the quadcopters composing trios. The existence of the control input satisfying NCBF conditions is analyzed by employing the characteristics of the power diagram. The proposed framework is synthesized with a coverage control law that maximizes the monitoring quality while reducing overlaps of FOVs. The proposed method is demonstrated in simulation and experiment.

This paper presents a coverage control algorithm for teams of quadcopters with downward facing visual sensors that prevents the appearance of coverage holes in-between the monitored areas while maximizing the coverage quality as much as possible. We derive necessary and sufficient conditions for preventing the appearance of holes in-between the fields of views among trios of robots. Because this condition can be expressed as logically combined constraints, control nonsmooth barrier functions are implemented to enforce it. An algorithm which extends control nonsmooth barrier functions to hybrid systems is implemented to manage the switching among barrier functions caused by the changes of the robots composing trio. The performance and validity of the proposed algorithm are evaluated in simulation as well as on a team of quadcopters.

This paper presents a coverage control strategy for teams of quadcopters that ensures that no area is left unsurveyed in between the fields of view of the visual sensors mounted on the quadcopters. We present a locational cost that quantifies the team's coverage performance according to the sensors' performance function. Moreover, the cost function penalizes overlaps between the fields of view of the different sensors, with the objective of increasing the area covered by the team. A distributed control law is derived for the quadcopters so that they adjust their position and zoom according to the direction of ascent of the cost. Control barrier functions are implemented to ensure that, while executing the gradient ascent control law, no holes appear in between the fields of view of neighboring robots. The performance of the algorithm is evaluated in simulated experiments.

This paper investigates passivity-based pose control via an obstacle avoidance navigation function for three-dimensional (3-D) eye-in-hand visual feedback systems. Firstly, visual motion observer-based pose control for 3-D eye-in-hand visual feedback systems is presented. Next, a path planner to be appropriate for the visual motion error system is designed through an obstacle avoidance navigation function to keep collision-free during servoing. Finally, the effectiveness of the proposed method is verified through computer simulations.

Conventional ground-penetrating radar (GPR) requires large-aperture antennas or long-span measurements to survey a remote location precisely. We propose a laser-driven GPR (LGPR) as a new detection method. LGPR uses microwaves from laser-produced plasmas as remote transmitters and can survey a remote location using a compact instrument. We performed numerical simulations to investigate the radiation mechanism of microwaves from laser plasmas and confirmed the pulsewidth of the laser suitable for LGPR. Experiments with subnanosecond pulse lasers clarified the feasibility and detection performance of LGPR.

This paper is concerned with a new type of robust tracking control scheme for robot manipulators using SP-D (saturated proportional and differential) feedback loops. The control scheme based on quasi-natural potential is generalized from set-point regulation to trajectory tracking by exploiting an effective auxiliary variable with positional and velocity errors. Without any uncertainties in the manipulator model, the tracking SP-D control scheme ensures globally asymptotic stability. In the presence of parametric model uncertainties, the proposed robust tracking controller is able to guarantee globally uniformly ultimate boundedness. Experimental results on the SICE standard manipulator show theoretical effectiveness of the robust tracking SP-D control.

An online character recognition system has been developed in order to allow effective Japanese entry via a pen interface. The system consists of handwriting recognition, contextual postprocessing, and enhanced Kana-to-Kanji conversion subsystems. The recognition subsystem uses a hybrid algorithm consisting of a pattern matching discriminator and a neural network verifier. Special care was taken to improve recognition of non-Kanji and simple Kanji characters frequently used in fast data entry. The postprocessor predicts consecutive characters on the basis of biagrams modified by the addition of parts of speech and substitution of macro characters for Kanji characters. A Kana-to-Kanji conversion method designed for ease of use with a pen interface is also integrated into the system. In an experiment in which 2499 samples of Kanji and non-Kanji characters were taken from 20 subjects, it was observed that the original recognition accuracy of 85% (the result obtained by using the pattern matching discriminator) was improved to 91.5% by adding the hybrid algorithm, and that it was further improved to 94.5% by adding the postprocessor. Improved recognition accuracy.>