In Japan, labor shortage of agriculture is becoming increasingly severe due to the lack of farmers and aging. Therefore, the development of automation of vegetable production such as transplanting, harvesting and transporting is required. In this paper, a self-localization method by using LiDAR and a robust control method of a transplanter are proposed for accurate transplanting. In this system, the path of transplanter is generated by using 3D point cloud data, and the transplanting part follows it and plant seedlings of cabbage accurately. Path generation is performed considering vehicle tilt in the roll direction depending on the environment of grooves. An accurate calculation of lateral and angular position of the transplanting part is also proposed. For path following control, sliding-mode control and inverse optimal control are applied to transplanter. The experimental results demonstrated the effectiveness of these proposed methods and problems we have to tackle on. Basically, it was possible to perform automated transplanting accurately, but there was an occasional problem of offset error from 0. It was confirmed that inverse optimal control is superior to sliding-mode control and is more robust to environmental changes.

The research of image-based control for nonholonomic mobile robots is a recent topic of mobile robots. There are few researches about image-based control of mobile robots with central catadioptric cameras. A central catadioptric camera is very effective to keep target objects in the camera field of view because of its wide area view. In this paper, a new image-based path following control method for a nonholonomic mobile robot with a central catadioptric camera is proposed in the image parameter space. It is confirmed by several simulation, indoor and outdoor experiments that the designed system has high performance and robustness in real world.

A design method of inverse optimal tracking controllers is proposed for nonholonomic mobile robots with two actuated wheels. In the inverse optimal control approach, a controller is designed by using a control Lyapunov function and Sontag's formula. The controller minimizes some meaningful cost dependent on the controller which is not given in advance, and the designed system has a stability margin which guarantees robustness with respect to input uncertainties. The robust property is a very important issue for real applications. Several simulation and experimental results show the ability of the proposed controller by comparing with an existing method.

An autonomous blimp for a surveillance system, which is circling around a specified target with only one camera, is designed in this paper. For this purpose, an extension of Lucas-Kanade algorithm for detection and tracking of features with rotation and scaling is provided, and a simplified structure-from-motion algorithm is applied to improve the accuracy of state estimation. A tracking controller is designed for the blimp which is an underactuated system. The desired path of the blimp is also generated from image information of a target. The blimp flies around the target automatically, after a commander sets it. Some experiments are performed indoors by using an aerial blimp.

A novel image-based visual approach for controlling nonholonomic mobile robots to track a moving target is presented. The mobile robot is endowed with a fixed camera, and a visual feedback controller is used to control the mobile robot to track a moving target of interest. A three dimensional state space representation of the camera-target visual interaction model fully defined in the image plane is used. In the case of an unknown height moving target symbol traced by camera, the global stability is proved using an adaptive backstepping control law. Based on the Lyapunov direct method, the closed-loop stability is guaranteed. Experimental results of a mobile robot with two actuated wheels equiped with a fixed camera are provided for illustrating the tracking ability of the controller.

A mobile robot is one of the well-known nonholonomic systems. The integration of a kinematic controller and a torque controller for the dynamic model of a nonholonomic mobile robot has been presented (Fierro and Lewis, 1995). In this paper, an adaptive extension of the controller is proposed. If an adaptive tracking controller for the kinematic model with unknown parameters exists, an adaptive tracking controller for the dynamic model with unknown parameters can be designed by using an adaptive backstepping approach. A design example for a mobile robot with two actuated wheels is provided. In this design, a new kinematic adaptive controller is proposed, then a torque adaptive controller is derived by using the kinematic controller.