Defining positioning in a core ontology for robotics

Unambiguous definition of spatial position and orientation has crucial importance for robotics. In this paper we propose an ontology about positioning. It is part of a more extensive core ontology being developed by the IEEE RAS Working Group on ontologies for robotics and automation. The core ontology should provide a common ground for further ontology development in the field. We give a brief overview of concepts in the core ontology and then describe an integrated approach for representing quantitative and qualitative position information.3-7 November 201

Proceedings of the 1st Standardized Knowledge Representation and Ontologies for Robotics and Automation Workshop

Welcome to IEEE-ORA (Ontologies for Robotics and Automation) IROS workshop. This is the 1st edition of the workshop on! Standardized Knowledge Representation and Ontologies for Robotics and Automation. The IEEE-ORA 2014 workshop was held on the 18th September, 2014 in Chicago, Illinois, USA. In!the IEEE-ORA IROS workshop, 10 contributions were presented from 7 countries in North and South America, Asia and Europe. The presentations took place in the afternoon, from 1:30 PM to 5:00 PM. The first session was dedicated to “Standards for Knowledge Representation in Robotics”, where presentations were made from the IEEE working group standards for robotics and automation, and also from the ISO TC 184/SC2/WH7. The second session was dedicated to “Core and Application Ontologies”, where presentations were made for core robotics ontologies, and also for industrial and robot assisted surgery ontologies. Three posters were presented in emergent applications of ontologies in robotics. We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this workshop. Next, to all the members of the international program committee, who helped us with their expertise and valuable time. We would also like to deeply thank the IEEE-IROS 2014 organizers for hosting this workshop. Our deep gratitude goes to the IEEE Robotics and Automation Society, that sponsors! the IEEE-ORA group activities, and also to the scientific organizations that kindly agreed to sponsor all the workshop authors work

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Intuitive Instruction of Industrial Robots : A Knowledge-Based Approach

With more advanced manufacturing technologies, small and medium sized enterprises can compete with low-wage labor by providing customized and high quality products. For small production series, robotic systems can provide a cost-effective solution. However, for robots to be able to perform on par with human workers in manufacturing industries, they must become flexible and autonomous in their task execution and swift and easy to instruct. This will enable small businesses with short production series or highly customized products to use robot coworkers without consulting expert robot programmers. The objective of this thesis is to explore programming solutions that can reduce the programming effort of sensor-controlled robot tasks. The robot motions are expressed using constraints, and multiple of simple constrained motions can be combined into a robot skill. The skill can be stored in a knowledge base together with a semantic description, which enables reuse and reasoning. The main contributions of the thesis are 1) development of ontologies for knowledge about robot devices and skills, 2) a user interface that provides simple programming of dual-arm skills for non-experts and experts, 3) a programming interface for task descriptions in unstructured natural language in a user-specified vocabulary and 4) an implementation where low-level code is generated from the high-level descriptions. The resulting system greatly reduces the number of parameters exposed to the user, is simple to use for non-experts and reduces the programming time for experts by 80%. The representation is described on a semantic level, which means that the same skill can be used on different robot platforms. The research is presented in seven papers, the first describing the knowledge representation and the second the knowledge-based architecture that enables skill sharing between robots. The third paper presents the translation from high-level instructions to low-level code for force-controlled motions. The two following papers evaluate the simplified programming prototype for non-expert and expert users. The last two present how program statements are extracted from unstructured natural language descriptions