In this paper, we propose a dynamic visual servo controller for precise tracking of robot manipulator. For the controller, we used a dual-loop structure which includes a vision controller and dynamic controller with different sampling speed. The vision controller is accommodated in the outer control loop with the aid of eye-in-hand camera, implementing the image based visual servoing method. As an inner loop controller, an adaptive backstepping controller is derived for position control of joint angle together with PID controller. The performance of proposed visual servo controller has been verified through computer simulation with V-REP simulation package.

This paper proposes a new SLAM (Simultaneous Localization and Mapping) algorithm based on hybrid map method. We express the environment surrounding mobile robot with a grid and a feature map. Using the reliability of estimation for individual map, we calculate the importance factor for Rao-Blackwellized Particle Filter (RBPF) resampling. In this way, we improve the accuracy of the algorithm and reduce computational complexity. Experimental results verify the feasibility and effectiveness of our algorithm.

In the present paper, a method is proposed that uses the geomagnetic field to estimate the positions of mobile robots in indoor environment. The reinforced concrete, H-beams, and power systems in buildings distort the geomagnetic field and these characteristics are used as regional features to estimate the positions of mobile robots. Another method is also proposed that prepares geomagnetic field maps using the model information obtained from the characteristics of sensors mounted on mobile robots and the position information to efficiently access the database. The extended Kalman filter is used to fuse robot motion models with geomagnetic field sensor models. The performance of the proposed algorithm is verified through Ground Truth experiments.

Schizotypy refers to a set of temporally stable personality traits that are observed in the general population and individuals with schizotypy showed deficit in emotion perception recognition. Schizotypy attacks about 10% of the general population and contributing about the emotional perceptions of these population can contributes a lot in the area of BCI to assist the victims. Hence we apply machine learning algorithms to classify schizotypy individuals from normal control groups and the impact of training on schizotypyed.

The advantage of a laser interferometer is in the high resolution it provides, especially in extremely sensitive nanometrology. The laser interferometer plays a crucial role in ultra‐precision measurement areas. However, the measurement accuracy is limited by a nonlinearity error. The nonlinearity error of the heterodyne laser interferometer needs to be compensated for. An H ∞ filter is applied to compensate for the nonlinearity error caused by the elliptic polarisation, two non‐orthogonal beams and an imperfect optical alignment. The proposed compensation method using an H ∞ filter can reduce the nonlinearity error. The experimental results show an improved accuracy and reliability.

This paper considers a design problem for time synchronized coverage control of cooperative mobile robots. The derived algorithm provides a coverage control which not only considers the mobility characteristic of each mobile robot for task allocation but generates robot velocity profile for synchronized coverage completion within the constrained time. Since the environment for robot coverage work is modeled as a set of locations to visit by robots, the derived coverage algorithm and its control method are equally well suited to an unstructured working environment as to the structured work space. In determining the number of locations for each robot to visit during coverage operation, a time index derived from the minimum time velocity profile is used for the comparison of robot performance. Once the set of locations has been determined for each robot, the corresponding path tree and velocity profile are generated for synchronized execution of coverage work. The completeness of synchronized group coverage within the constrained time is proven through simulation for a group of mobile robots with different motor characteristics. An additional consideration by the derived coverage controller is collision avoidance of mobile robots in a crowded environment with the aid of finite potential function approach.

In this paper, we propose a dynamic visual servo controller for precise tracking of robot manipulator. For the controller, we used a dual-loop structure which includes a vision controller and dynamic controller with different sampling speed. The vision controller is accommodated in the outer control loop with the aid of eye-in-hand camera, implementing the image based visual servoing method. As an inner loop controller, an adaptive backstepping controller is derived for position control of joint angle together with PID controller. The performance of proposed visual servo controller has been verified through computer simulation with V-REP simulation package.

This paper proposes a new SLAM (Simultaneous Localization and Mapping) algorithm based on hybrid map method. We express the environment surrounding mobile robot with a grid and a feature map. Using the reliability of estimation for individual map, we calculate the importance factor for Rao-Blackwellized Particle Filter (RBPF) resampling. In this way, we improve the accuracy of the algorithm and reduce computational complexity. Experimental results verify the feasibility and effectiveness of our algorithm.