Small robot agents with on-board vision and local intelligence

We designed a family of completely autonomous mobile robots with local intelligence. We developed a controller with a variety of digital and analog I/O facilities and the operating system RoBIOS, which allows maximum flexibility. The robots have a number of on-board sensors, including vision, and do not rely on global sensor systems. The on-board computing power is sufficient to analyze several color images per second. This enables the robots to perform several different task such as navigation, map generation or intelligent group behavior and does not limit them to the game of robot soccer.     

Moment feature-based three-dimensional tracking using two high-speed vision systems

When considering real-world applications of robot control with visual servoing, both three-dimensional (3-D) information and a high feedback rate are required. We have developed a 3-D target-tracking system with a 1-ms feedback rate using two high-speed vision systems called Column Parallel Vision (CPV) systems. To obtain 3-D information, such as position, orientation and shape parameters of the target object, a feature-based algorithm has been introduced using moment feature values extracted from vision systems for a spheroidal object model. Also, we propose a new 3-D self-windowing method to extract the target in 3-D space using epipolar geometry, which is an extension of the conventional self-windowing method in 2-D images.     

A 10-gram vision-based flying robot

We aim at developing ultralight autonomous microflyers capable of freely flying within houses or small built environments while avoiding collisions. Our latest prototype is a fixed-wing aircraft weighing a mere 10 g, flying around 1.5 m/s, and carrying the necessary electronics for airspeed regulation and lateral collision avoidance. This microflyer is equipped with two tiny camera modules, two rate gyroscopes, an anemometer, a small microcontroller and a Bluetooth radio module. In-flight tests were carried out in a new experimentation room specifically designed for easy changing of surrounding textures.     

机器视觉在基片自动分类机中的应用

介绍了机器视觉的基本原理、组成结构及其在自行研制的基片自动分类机中的应用，展示了面阵CCD在基片自动分类机视觉系统中的重要作用。     

Super-resolution for an omnidirectional vision sensor

A prominent emerging theory of sensorimotor development in biological systems proposes that control knowledge is encoded in the dynamics of physical interaction with the world. From this perspective, the musculoskeletal system is coupled through sensor feedback and neurological structure to a non-stationary world. Control is derived by reinforcing and learning to predict constructive patterns of interaction. We have adopted the traditions of dynamic pattern theory in which behavior is an artifact of coupled dynamical systems with a number of controllable degrees of freedom. For grasping and manipulation, we propose a closed-loop control process that is parametric in the number and identity of contact resources. We have shown previously that this controller generates a necessary condition for force closure grasps. In this paper, we will show how control decisions can be made by estimating patterns of membership in a family of prototypical dynamic models. A grasp controller can thus be tuned on-line to optimize performance over a variety of object geometries. This same process can be used to match the dynamics to several previously acquired haptic categories. We will illustrate how a grasping policy can be acquired that is incrementally optimal for several objects using our Salisbury hand with tactile sensor feedback.     

Robot Localization in Indoor Environments Using Radio Frequency Identification Technology and Stereo Vision

In this paper, a novel method of obstacle recognition and localization for mobile robots using radio frequency identification (RFID) technology and stereo vision is proposed. It is inexpensive, flexible and easy to use in practical environments. As information about the obstacles or environment can be written in ID tags, the proposed method can detect the obstacles easily and quickly compared with other methods. RF is not so stable, so the Bayes rule was introduced to calculate the probability where the ID tag exists in order to improve the accuracy of localizing obstacles with the ID tags. Then the stereo camera starts to process the image of the region of interest where the obstacle exists. The proposed method does not need to process all the image and easily gets some information about obstacles such as size, and color, and thus decreases the processing computation. Research on RFID technology integrating stereo vision to localize an indoor mobile robot has also been performed. This paper introduces the architecture of the proposed method and some experimental results.     

Coordination of Multiple Control Schemes for Mobile Robot Navigation on the Basis of the Generalized Stochastic Petri-Nets

There have been two major streams of research for the motion control of mobile robots: model-based deliberate control and sensor-based reactive control. Since the two schemes have complementary advantages and disadvantages, each cannot completely replace the other. There are a variety of environmental conditions that affect the performance of navigation. The motivation of this study is that multiple motion control schemes are required to survive in dynamic real environments. In this paper, we exploit two discrete motion controllers for mobile robots. One is the deliberate trajectory tracking controller and the other is the reactive dynamic window approach. We propose the selective coordination of two controllers on the basis of the generalized stochastic Petri net (GSPN) framework. The major scope of this paper is to clarify the advantage of the proposed controller based on the coordination of multiple controllers from the results of quantitative performance comparison among motion controllers. For quantitative comparison, both simulations and experiments in dynamic environments were carried out. In addition, it is shown that navigation experiences are accumulated in the GSPN formalism. The performance of navigation service can be significantly improved owing to the automatically stored experiences.     

Autonomous Vehicle Control Using Lidar and Camera with CAN Network

An autonomous vehicle operates in a dynamically changing environment,where multiple sensors must work in a cooperative mode. In these scenarios reliability of t...     

Towards terrain-aided navigation for underwater robotics

This paper describes an approach to autonomous navigation for an undersea vehicle that uses information from a scanning sonar to generate navigation estimates based on a simultaneous localization and mapping algorithm. Development of low-speed platform models for vehicle control and the theoretical and practical details of mapping and position estimation using sonar are provided. An implementation of these techniques on a small submersible vehicle 'Oberon' are presented.