Monocular Vision as a Range Sensor

One of the most important abilities for a mobile robot is detecting obstacles in order to avoid collisions. Building a map of these obstacles is the next logical step. Most robots to date have used sensors such as passive or active infrared, sonar or laser range finders to locate obstacles in their path. In contrast, this work uses a single colour camera as the only sensor, and consequently the robot must obtain range information from the camera images. We propose simple methods for determining the range to the nearest obstacle in any direction in the robot’s field of view, referred to as the Radial Obstacle Profile. The ROP can then be used to determine the amount of rotation between two successive images, which is important for constructing a 360º view of the surrounding environment as part of map construction

AUV SLAM and experiments using a mechanical scanning forward-looking sonar

Navigation technology is one of the most important challenges in the applications of autonomous underwater vehicles (AUVs) which navigate in the complex undersea environment. The ability of localizing a robot and accurately mapping its surroundings simultaneously, namely the simultaneous localization and mapping (SLAM) problem, is a key prerequisite of truly autonomous robots. In this paper, a modified-FastSLAM algorithm is proposed and used in the navigation for our C-Ranger research platform, an open-frame AUV. A mechanical scanning imaging sonar is chosen as the active sensor for the AUV. The modified-FastSLAM implements the update relying on the on-board sensors of C-Ranger. On the other hand, the algorithm employs the data association which combines the single particle maximum likelihood method with modified negative evidence method, and uses the rank-based resampling to overcome the particle depletion problem. In order to verify the feasibility of the proposed methods, both simulation experiments and sea trials for C-Ranger are conducted. The experimental results show the modified-FastSLAM employed for the navigation of the C-Ranger AUV is much more effective and accurate compared with the traditional methods

Competing in the RoboCup Rescue Robot League

RoboCup Rescue is an international competition in which robots compete to find disaster victims in a simulated earthquake environment. It features both a Rescue Simulation League (RSL) which is entirely computer simulated, and a Rescue Robot League (RRL) with real robots and a test arena. This paper will describe the experience gained sending an undergraduate team to compete in the Rescue Robot League at the RoboCup German Open in 2008 and 2009. The design of the test arena and the rules of the competition will be outlined; as will the approaches taken by different teams; and the competition results

Navigation system for a mobile robot incorporating trinocular vision for range imaging

This research focuses on the development of software for the navigation of a mobile robot. The software developed to control the robot uses sensory data obtained from ultra sound, infra red and tactile sensors, along with depth maps using trinocular vision. Robot navigation programs were written to navigate the robot and were tested in a simulated environment as well as the real world. Data from the various sensors was read and successfully utilized in the control of the robot motion. Software was developed to obtain the range and bearing of the closest obstacle in sight using the trinocular vision system. An operator supervised navigation system was also developed that enabled the navigation of the robot based on the inference from the camera images

Design and development of an autonomous duct inspection and mapping robot

Just a few years ago, the idea of having robots in factories and households was science fiction. But, as robotic technology develops, this is becoming reality. Nowadays, robots not only perform simple household chores, but are used in most production lines and are even employed by the army. Visual inspection robots are very common and are used in many industries, including inspecting the interior of duct systems. Duct systems are in place in almost all large buildings and require ongoing maintenance and cleaning. Systems that are not properly maintained can pose a health risk as dust and mold form and are then blown throughout the building. In some cases, access holes have to be cut to allow access for inspection to occur. A robotic system, small enough to enter a duct through any existing access panel, would be advantageous. An autonomous robot would be even more useful as no operator would be needed thus reducing operating costs. To this end, a robot was developed that could autonomously navigate through a duct system, recoding video images and mapping the internal profile. The development of which is discussed in this thesis, included the design of the robotic platform, the inclusion of appropriate sensors and accompanying circuitry, generation of a simulation to test the control algorithm and implementing embedded software to control the robot. From the testing of the entire system the following conclusions were drawn. The robot as a whole performed well and navigated autonomously through the duct with a success rate of 90%. The system tests were repeatable and the odometry data closely matched the actual paths for straight line travel. The sonar data closely corresponded to the duct walls but was hard to interpret when the odometry and actual paths diverged. These paths diverged from each other due to wheel slip caused as the robot turned. The simulation developed showed that the control algorithm would ensure that the robot recursively inspected any duct system and provided information about the system as a whole. Further work should concentrate on improving the correlation between the odometry path and the actual path, perhaps by adding in a bearing measurement system. Sensors with greater range and accuracy should be implemented and the entire system re-tested. The embedded controller allowed for expansion should additional requirements be needed and was more then adequate for the task

Deictic primitives for general purpose navigation

A visually-based deictic primative used as an elementary command set for general purpose navigation was investigated. It was shown that a simple 'follow your eyes' scenario is sufficient for tracking a moving target. Limitations of velocity, acceleration, and modeling of the response of the mechanical systems were enforced. Realistic paths of the robots were produced during the simulation. Scientists could remotely command a planetary rover to go to a particular rock formation that may be interesting. Similarly an expert at plant maintenance could obtain diagnostic information remotely by using deictic primitives on a mobile are used in the deictic primitives, we could imagine that the exact same control software could be used for all of these applications