Terrain-Based Navigation for Underwater Vehicles Using an Ultrasonic Scanning System

In this paper an approach to the field of outdoor robotic navigation with a focus on underwater simultaneous localization and mapping (SLAM) is proposed that utilizes ultrasonic scanning images. Experimental results from the implementation of a SLAM algorithm with real data are presented. The projected landmark detection process constructs a map of the environment and generates navigation estimates based on an adaptive delayed nearest-neighbor algorithm. The feature extraction and validation processes are resolved at the sensor level using a simple local maximum-level detection algorithm on the range data. This paper presents experimental results from our research efforts in the above area, using data from water tank trials and a remotely operated vehicle operating in a shallow water environment.     

Kinematics-Based Navigation Functions

In this paper, we introduce a new family of navigation laws which are based on analytic navigation functions derived using the kinematics equations. These navigation laws combine local and global aspects, and can be used for both indoor and outdoor navigation. The robot's kinematics model is represented in polar coordinates. The analytic navigation functions suggested here are functions of the line-of-sight angle between the robot and the goal, and depend on one or more navigation parameters. The navigation parameters allow us to control the navigation law and, thus, the path of the robot. The choice of the navigation function and its parameters is important, and must satisfy some conditions. Different paths are obtained for different navigation functions and different parameters. This property is used to avoid collision with obstacles. Under this formulation, the number of navigation functions allowing the robot to reach a given goal is infinite. An extensive simulation study shows the effectiveness of the method.     

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.     

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.     

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.     

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。     

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...     

Design and Implementation of a Novel Outdoor Road-Cleaning Robot

In order to clean unknown outdoor environments, we devised a novel outdoor cleaning robot using mainly on-board vision-based auto-navigation in this paper. The track-driven and cleaning mechanisms of the robot are designed for cleaning tasks in outdoor rough terrain. A single image sensing module is exploited for clean-region detection and three ultrasonic ranging modules are used for obstacle avoidance. The cleaning task is performed autonomously after the boustrophedon path planning is completed in the grid-cell map. The map is obtained from transforming the two-dimensional images captured by the image sensor. The robot also self-localizes based on the deduced boundary lines at the end of each cleaning stage to continue its unfinished cleaning work. The experimental results prove that our outdoor cleaning robot performs well in general outdoor environments.     

A micro-rover navigation and control system for autonomous planetary exploration

This paper describes an end-to-end control system for autonomous navigation of a small vehicle at a remote place, e.g. in space for planetary exploration. Due to a realistic background of this study the proposed method has to deal with limited knowledge about the environment as well as limited system resources and operational boundary conditions, especially a very large time delay in the communication between the ground control station and the space segment. To overcome these constraints the remote system has to act in a very autonomous way. Ground support minimizes the computational load of the remote system. High-level information interchange reduces the communication bandwidth requirements.