WiDEVIEW: An UltraWideBand and Vision Dataset for Deciphering Pedestrian-Vehicle Interactions

Robust and accurate tracking and localization of road users like pedestrians and cyclists is crucial to ensure safe and effective navigation of Autonomous Vehicles (AVs), particularly so in urban driving scenarios with complex vehicle-pedestrian interactions. Existing datasets that are useful to investigate vehicle-pedestrian interactions are mostly image-centric and thus vulnerable to vision failures. In this paper, we investigate Ultra-wideband (UWB) as an additional modality for road users' localization to enable a better understanding of vehicle-pedestrian interactions. We present WiDEVIEW, the first multimodal dataset that integrates LiDAR, three RGB cameras, GPS/IMU, and UWB sensors for capturing vehicle-pedestrian interactions in an urban autonomous driving scenario. Ground truth image annotations are provided in the form of 2D bounding boxes and the dataset is evaluated on standard 2D object detection and tracking algorithms. The feasibility of UWB is evaluated for typical traffic scenarios in both line-of-sight and non-line-of-sight conditions using LiDAR as ground truth. We establish that UWB range data has comparable accuracy with LiDAR with an error of 0.19 meters and reliable anchor-tag range data for up to 40 meters in line-of-sight conditions. UWB performance for non-line-of-sight conditions is subjective to the nature of the obstruction (trees vs. buildings). Further, we provide a qualitative analysis of UWB performance for scenarios susceptible to intermittent vision failures. The dataset can be downloaded via https://github.com/unmannedlab/UWB_Dataset

DEVELOPMENT OF AN AUTONOMOUS NAVIGATION SYSTEM FOR THE SHUTTLE CAR IN UNDERGROUND ROOM & PILLAR COAL MINES

In recent years, autonomous solutions in the multi-disciplinary field of the mining engineering have been an extremely popular applied research topic. The growing demand for mineral supplies combined with the steady decline in the available surface reserves has driven the mining industry to mine deeper underground deposits. These deposits are difficult to access, and the environment may be hazardous to mine personnel (e.g., increased heat, difficult ventilation conditions, etc.). Moreover, current mining methods expose the miners to numerous occupational hazards such as working in the proximity of heavy mining equipment, possible roof falls, as well as noise and dust. As a result, the mining industry, in its efforts to modernize and advance its methods and techniques, is one of the many industries that has turned to autonomous systems. Vehicle automation in such complex working environments can play a critical role in improving worker safety and mine productivity. One of the most time-consuming tasks of the mining cycle is the transportation of the extracted ore from the face to the main haulage facility or to surface processing facilities. Although conveyor belts have long been the autonomous transportation means of choice, there are still many cases where a discrete transportation system is needed to transport materials from the face to the main haulage system. The current dissertation presents the development of a navigation system for an autonomous shuttle car (ASC) in underground room and pillar coal mines. By introducing autonomous shuttle cars, the operator can be relocated from the dusty, noisy, and potentially dangerous environment of the underground mine to the safer location of a control room. This dissertation focuses on the development and testing of an autonomous navigation system for an underground room and pillar coal mine. A simplified relative localization system which determines the location of the vehicle relatively to salient features derived from on-board 2D LiDAR scans was developed for a semi-autonomous laboratory-scale shuttle car prototype. This simplified relative localization system is heavily dependent on and at the same time leverages the room and pillar geometry. Instead of keeping track of a global position of the vehicle relatively to a fixed coordinates frame, the proposed custom localization technique requires information regarding only the immediate surroundings. The followed approach enables the prototype to navigate around the pillars in real-time using a deterministic Finite-State Machine which models the behavior of the vehicle in the room and pillar mine with only a few states. Also, a user centered GUI has been developed that allows for a human user to control and monitor the autonomous vehicle by implementing the proposed navigation system. Experimental tests have been conducted in a mock mine in order to evaluate the performance of the developed system. A number of different scenarios simulating common missions that a shuttle car needs to undertake in a room and pillar mine. The results show a minimum success ratio of 70%

Satellite Navigation for the Age of Autonomy

Global Navigation Satellite Systems (GNSS) brought navigation to the masses. Coupled with smartphones, the blue dot in the palm of our hands has forever changed the way we interact with the world. Looking forward, cyber-physical systems such as self-driving cars and aerial mobility are pushing the limits of what localization technologies including GNSS can provide. This autonomous revolution requires a solution that supports safety-critical operation, centimeter positioning, and cyber-security for millions of users. To meet these demands, we propose a navigation service from Low Earth Orbiting (LEO) satellites which deliver precision in-part through faster motion, higher power signals for added robustness to interference, constellation autonomous integrity monitoring for integrity, and encryption / authentication for resistance to spoofing attacks. This paradigm is enabled by the 'New Space' movement, where highly capable satellites and components are now built on assembly lines and launch costs have decreased by more than tenfold. Such a ubiquitous positioning service enables a consistent and secure standard where trustworthy information can be validated and shared, extending the electronic horizon from sensor line of sight to an entire city. This enables the situational awareness needed for true safe operation to support autonomy at scale.Comment: 11 pages, 8 figures, 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS

Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions

Welcome to ROBOTICA 2009. This is the 9th edition of the conference on Autonomous Robot Systems and Competitions, the third time with IEEE‐Robotics and Automation Society Technical Co‐Sponsorship. Previous editions were held since 2001 in Guimarães, Aveiro, Porto, Lisboa, Coimbra and Algarve. ROBOTICA 2009 is held on the 7th May, 2009, in Castelo Branco , Portugal. ROBOTICA has received 32 paper submissions, from 10 countries, in South America, Asia and Europe. To evaluate each submission, three reviews by paper were performed by the international program committee. 23 papers were published in the proceedings and presented at the conference. Of these, 14 papers were selected for oral presentation and 9 papers were selected for poster presentation. The global acceptance ratio was 72%. After the conference, eighth papers will be published in the Portuguese journal Robótica, and the best student paper will be published in IEEE Multidisciplinary Engineering Education Magazine. Three prizes will be awarded in the conference for: the best conference paper, the best student paper and the best presentation. The last two, sponsored by the IEEE Education Society ‐ Student Activities Committee. We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this conference. Next, to all the members of the international program committee and reviewers, who helped us with their expertise and valuable time. We would also like to deeply thank the invited speaker, Jean Paul Laumond, LAAS‐CNRS France, for their excellent contribution in the field of humanoid robots. Finally, a word of appreciation for the hard work of the secretariat and volunteers. Our deep gratitude goes to the Scientific Organisations that kindly agreed to sponsor the Conference, and made it come true. We look forward to seeing more results of R&D work on Robotics at ROBOTICA 2010, somewhere in Portugal

Bridge Inspection: Human Performance, Unmanned Aerial Systems and Automation

Unmanned aerial systems (UASs) have become of considerable private and commercial interest for a variety of jobs and entertainment in the past 10 years. This paper is a literature review of the state of practice for the United States bridge inspection programs and outlines how automated and unmanned bridge inspections can be made suitable for present and future needs. At its best, current technology limits UAS use to an assistive tool for the inspector to perform a bridge inspection faster, safer, and without traffic closure. The major challenges for UASs are satisfying restrictive Federal Aviation Administration regulations, control issues in a GPS-denied environment, pilot expenses and availability, time and cost allocated to tuning, maintenance, post-processing time, and acceptance of the collected data by bridge owners. Using UASs with self-navigation abilities and improving image-processing algorithms to provide results near real-time could revolutionize the bridge inspection industry by providing accurate, multi-use, autonomous three-dimensional models and damage identification