Development of a piecewise linear omnidirectional 3D image registration method.

This paper proposes a new piecewise linear omnidirectional image registration method. The proposed method segments an image captured by multiple cameras into 2D segments defined by feature points of the image and then stitches each segment geometrically by considering the inclination of the segment in the 3D space. Depending on the intended use of image registration, the proposed method can be used to improve image registration accuracy or reduce the computation time in image registration because the trade-off between the computation time and image registration accuracy can be controlled for. In general, nonlinear image registration methods have been used in 3D omnidirectional image registration processes to reduce image distortion by camera lenses. The proposed method depends on a linear transformation process for omnidirectional image registration, and therefore it can enhance the effectiveness of the geometry recognition process, increase image registration accuracy by increasing the number of cameras or feature points of each image, increase the image registration speed by reducing the number of cameras or feature points of each image, and provide simultaneous information on shapes and colors of captured objects.

Symmetric caging formation for convex polygonal object transportation by multiple mobile robots based on fuzzy sliding mode control.

In this paper, the problem of object caging and transporting is considered for multiple mobile robots. With the consideration of minimizing the number of robots and decreasing the rotation of the object, the proper points are calculated and assigned to the multiple mobile robots to allow them to form a symmetric caging formation. The caging formation guarantees that all of the Euclidean distances between any two adjacent robots are smaller than the minimal width of the polygonal object so that the object cannot escape. In order to avoid collision among robots, the parameter of the robots radius is utilized to design the caging formation, and the A⁎ algorithm is used so that mobile robots can move to the proper points. In order to avoid obstacles, the robots and the object are regarded as a rigid body to apply artificial potential field method. The fuzzy sliding mode control method is applied for tracking control of the nonholonomic mobile robots. Finally, the simulation and experimental results show that multiple mobile robots are able to cage and transport the polygonal object to the goal position, avoiding obstacles.

A switching formation strategy for obstacle avoidance of a multi-robot system based on robot priority model.

This paper describes a switching formation strategy for multi-robots with velocity constraints to avoid and cross obstacles. In the strategy, a leader robot plans a safe path using the geometric obstacle avoidance control method (GOACM). By calculating new desired distances and bearing angles with the leader robot, the follower robots switch into a safe formation. With considering collision avoidance, a novel robot priority model, based on the desired distance and bearing angle between the leader and follower robots, is designed during the obstacle avoidance process. The adaptive tracking control algorithm guarantees that the trajectory and velocity tracking errors converge to zero. To demonstrate the validity of the proposed methods, simulation and experiment results present that multi-robots effectively form and switch formation avoiding obstacles without collisions.