A Study on Recent Developments and Issues with Obstacle Detection Systems for Automated Vehicles

This paper reviews current developments and discusses some critical issues with obstacle detection systems for automated vehicles. The concept of autonomous driving is the driver towards future mobility. Obstacle detection systems play a crucial role in implementing and deploying autonomous driving on our roads and city streets. The current review looks at technology and existing systems for obstacle detection. Specifically, we look at the performance of LIDAR, RADAR, vision cameras, ultrasonic sensors, and IR and review their capabilities and behaviour in a number of different situations: during daytime, at night, in extreme weather conditions, in urban areas, in the presence of smooths surfaces, in situations where emergency service vehicles need to be detected and recognised, and in situations where potholes need to be observed and measured. It is suggested that combining different technologies for obstacle detection gives a more accurate representation of the driving environment. In particular, when looking at technological solutions for obstacle detection in extreme weather conditions (rain, snow, fog), and in some specific situations in urban areas (shadows, reflections, potholes, insufficient illumination), although already quite advanced, the current developments appear to be not sophisticated enough to guarantee 100% precision and accuracy, hence further valiant effort is needed

Modelling of a Braitenberg inspired guidance system for an Autonomous surface vessel (ASV)

Master's thesis in Mechatronics (MAS500

PRECISE LANDING OF VTOL UAVS USING A TETHER

Unmanned Aerial Vehicles (UAVs), also known as drones, are often considered the solution to complex robotics problems. The significant freedom to explore an environment is a major reason why UAVs are a popular choice for automated solutions. UAVs, however, have a very limited flight time due to the low capacity and weight ratio of current batteries. One way to extend the vehicles\u27 flight time is to use a tether to provide power from external batteries, generators on the ground, or another vehicle. Attaching a tether to a vehicle may constrain its navigation but it may also create some opportunities for improvement of some tasks, such as landing. A tethered UAV can still explore an environment, but with some additional limitations: the tether can become wrapped around or bent by an obstacle, stopping the drone from traveling further and requiring backtracking to undo; the tether can fall loose and get caught while dragging on the ground; or the base of the tether could be mobile and the UAV needs to have a way to return to it. Most issues, like those listed above, could be solved with a vision system and various kinds of markers, but this approach could not work in situations of low light, where cameras are no longer effective. In this project, a state machine was developed to land a tethered, vertical take-off and landing (VTOL) UAV using only angles taken from both ends of the tether, the tension in the tether, and the height of the UAV. The main scenarios focused on in this project were normal operation, obstacle interference, loose tether, and a moving base. Normal operation is essentially tether guidance using the tether as a direction back to the base. The obstacle case has to determine the best action for untangling the tether. The loose tether case has to handle the loss of information given by the angle sensors, as the tether direction is no longer available. This case is performed as a last-ditched effort to find the landing pad with only a moderate chance for success. Lastly, the moving base case uses the change in the angles over time to determine the speed needed to reach the base. The software was not the only focus of this project. Two hardware components of this project were a landing platform and a matching landing gear to support the landing process. These two components were designed to aid in the precision of the landed location and to ensure that the UAV was secured in position once landed. The landing platform was designed as a passive funnel-type positioning mechanism with a depression in the center that the landing gear was designed to match. The tension of the tether is used to further lock the UAV into place when in motion. While some of this project remained theoretical, particularly the moving base case, there was flight testing performed for validation of most states of the proposed state machine. The normal operation state was effective at guiding the UAV onto the landing pad. The loose tether case was also able to land within reasonable expectations. This case was not always successful at finding the landing pad. Particular methods of increasing the likelihood of success are discussed in Future Work. The Obstacle Case was also able to be detected, but the response action has yet to be tested in full. The prior testing of velocity following can be used as proof of concept due to its simplicity. In conclusion, this project successfully developed a state machine for precisely landing a tethered UAV with no environmental knowledge or localization. Further development is necessary to improve the likelihood of landing in problematic scenarios and more testing is necessary for the system as a whole. More landing scenarios could also be researched and added as cases to the state machine to increase the robustness of the landing process. However, each current subsystem achieved some level of validation and is to be improved with future developments

Improving the mobility performance of autonomous unmanned ground vehicles by adding the ability to 'Sense/Feel' their local environment.

This paper follows on from earlier work detailed in output one and critically reviews the sensor technologies used in autonomous vehicles, including robots, to ascertain the physical properties of the environment including terrain sensing. The paper reports on a comprehensive study done in terrain types and how these could be determined and the appropriate sensor technologies that can be used. It also reports on work currently in progress in applying these sensor technologies and gives details of a prototype system built at Middlesex University on a reconfigurable mobility system, demonstrating the success of the proposed strategies. This full paper was subject to a blind refereed review process and presented at the 12th HCI International 2007, Beijing, China, incorporating 8 other international thematic conferences. The conference involved over 250 parallel sessions and was attended by 2000 delegates. The conference proceedings are published by Springer in a 17 volume paperback book edition in the Lecture Notes in Computer Science series (LNCS). These are available on-line through the LNCS Digital Library, readily accessible by all subscribing libraries around the world, published in the proceedings of the Second International Conference on Virtual Reality, ICVR 2007, held as Part of HCI International 2007, Beijing, China, July 22-27, 2007. It is also published as a collection of 81 papers in Lecture Notes in Computer Science Series by Springer