Real-Time Visual Feedback Control of Multi-Camera UAV

Recently, flight control of unmanned aerial vehicles (UAVs) in non-global positioning system (GPS) environments has become increasingly important. In such an environment, visual sensors are important, and their main roles are self-localization and obstacle avoidance. In this paper, the concept of a multi-camera UAV system with multiple cameras attached to the body is proposed to realize high-precision omnidirectional visual recognition, self-localization, and obstacle avoidance simultaneously, and a two-camera UAV is developed as a prototype. The proposed flight control system can switch between visual servoing (VS) for collision avoidance and visual odometry (VO) for self-localization. The feasibility of the proposed control system was verified by conducting flight experiments with the insertion of obstacles.

Development of a Real-Time Human-Robot Collaborative System Based on 1 kHz Visual Feedback Control and Its Application to a Peg-in-Hole Task

In this research, we focused on Human-Robot collaboration. There were two goals: (1) to develop and evaluate a real-time Human-Robot collaborative system, and (2) to achieve concrete tasks such as collaborative peg-in-hole using the developed system. We proposed an algorithm for visual sensing and robot hand control to perform collaborative motion, and we analyzed the stability of the collaborative system and a so-called collaborative error caused by image processing and latency. We achieved collaborative motion using this developed system and evaluated the collaborative error on the basis of the analysis results. Moreover, we aimed to realize a collaborative peg-in-hole task that required a system with high speed and high accuracy. To achieve this goal, we analyzed the conditions required for performing the collaborative peg-in-hole task from the viewpoints of geometric, force and posture conditions. Finally, in this work, we show the experimental results and data of the collaborative peg-in-hole task, and we examine the effectiveness of our collaborative system.

Visual Feedback Control of a Rat Ankle Angle Using a Wirelessly Powered Two-Channel Neurostimulator

Peripheral nerve disconnections cause severe muscle atrophy and consequently, paralysis of limbs. Reinnervation of denervated muscle by transplanting motor neurons and applying Functional Electrical Stimulation (FES) onto peripheral nerves is an important procedure for preventing irreversible degeneration of muscle tissues. After the reinnervation of denervated muscles, multiple peripheral nerves should be stimulated independently to control joint motion and reconstruct functional movements of limbs by the FES. In this study, a wirelessly powered two-channel neurostimulator was developed with the purpose of applying selective FES to two peripheral nerves—the peroneal nerve and the tibial nerve in a rat. The neurostimulator was designed in such a way that power could be supplied wirelessly, from a transmitter coil to a receiver coil. The receiver coil was connected, in turn, to the peroneal and tibial nerves in the rat. The receiver circuit had a low pass filter to allow detection of the frequency of the transmitter signal. The stimulation of the nerves was switched according to the frequency of the transmitter signal. Dorsal/plantar flexion of the rat ankle joint was selectively induced by the developed neurostimulator. The rat ankle joint angle was controlled by changing the stimulation electrode and the stimulation current, based on the Proportional Integral (PI) control method using a visual feedback control system. This study was aimed at controlling the leg motion by stimulating the peripheral nerves using the neurostimulator.