Robot autonome

vignette|exemple de robot autonome de type rover Un robot autonome, également appelé simplement autorobot ou autobot, est un robot qui exécute des comportements ou des tâches avec un degré élevé d'autonomie (sans influence extérieure). La robotique autonome est généralement considérée comme un sous-domaine de l'intelligence artificielle, de la robotique et de l'. Les premières versions ont été proposées et démontrées par l'auteur/inventeur David L. Heiserman. Les robots autonomes sont particulièrement souhaitables dans des domaines tels que les vols spatiaux, l'entretien ménager (comme le nettoyage), le traitement des eaux usées et la fourniture de biens et de services. Certains robots d'usine modernes sont "autonomes" dans les limites strictes de leur environnement direct. Il se peut que tous les degrés de liberté n'existent pas dans leur environnement, mais le lieu de travail du robot d'usine est difficile et peut souvent contenir des variables chaotiques et imprévisibles. Il faut

Functional and Adaptive Construction for Rescue

Hadi Ardiny

Although recent advances in the field of robotics have greatly increased robotic capabilities for several applications, autonomous robots are still in their infancy regarding their support of onsite construction. Unlike production robots that are used, for instance, in automotive industries, autonomous robotic systems should be designed with special considerations, such as the complexity of the cluttered and dynamic working space, inaccuracy in positioning because of the nature of mobile systems, and so forth. Thus, construction has been known as a highly complex application field for robotic systems, especially in unknown environments. In this thesis, we focus on the developments of an autonomous construction system by taking inspiration from architectural designs found in the animal kingdom. The construction system allows robots to build functional structures over a different range of environmental conditions or in unknown sites without the use of any predefined construction plan (i.e., blueprint). We call this approach adaptive and functional autonomous construction (AFAC). Indeed, AFAC is a robust and intelligent system that can tackle unforeseen problems of unknown environments and faults made during the course of building. We present two approaches for AFAC. One is a local approach that enables robots to locally sense features of their environment and then act immediately according to defined rules without using any global representation or knowledge of the world. Second is a global approach, which involves building structures by analysing global representations and knowledge produced by the robots. This approach consists of three phases: the first phase is exploration, to map the unknown environment and to find important elements. In the second phase, an effective construction plan is autonomously computed using collected data and the defined functions. Finally, in the last phase, the robot builds structures based on the computed construction plan. One interesting implementation of the introduced construction system is its potential use in a post disaster environment, where an autonomous robotic system can perform construction tasks in the rescue operation. Robots can be employed to build protective structures for rescue functions, including stabilizing large structures or protecting victims in unknown environments, where the environment are perhaps covered by debris. Inasmuch as the robots cannot plan in advance to build these structures, the rescue application is a well suited case for the study and implementation of AFAC in unknown and cluttered environments. Through implementation of AFAC in the rescue situations, we develop AFAC from scratch to the level at which the robots can autonomously apply AFAC's principles for use in the new classes of construction applications. We also study and compare the local and global approaches of AFAC. In addition, we develop new exploration methods and construction plan computation methodologies for the global approach to efficiently lead AFAC.

EPFL2017

Requirements for building an ontology for autonomous robots

Howard Li, Kamilo Andres Melo Becerra

Purpose - IEEE Ontologies for Robotics and Automation Working Group were divided into subgroups that were in charge of studying industrial robotics, service robotics and autonomous robotics. This paper aims to present the work in-progress developed by the autonomous robotics (AuR) subgroup. This group aims to extend the core ontology for robotics and automation to represent more specific concepts and axioms that are commonly used in autonomous robots. Design/methodology/approach - For autonomous robots, various concepts for aerial robots, underwater robots and ground robots are described. Components of an autonomous system are defined, such as robotic platforms, actuators, sensors, control, state estimation, path planning, perception and decision-making. Findings - AuR has identified the core concepts and domains needed to create an ontology for autonomous robots. Practical implications - AuR targets to create a standard ontology to represent the knowledge and reasoning needed to create autonomous systems that comprise robots that can operate in the air, ground and underwater environments. The concepts in the developed ontology will endow a robot with autonomy, that is, endow robots with the ability to perform desired tasks in unstructured environments without continuous explicit human guidance. Originality/value - Creating a standard for knowledge representation and reasoning in autonomous robotics will have a significant impact on all R&A domains, such as on the knowledge transmission among agents, including autonomous robots and humans. This tends to facilitate the communication among them and also provide reasoning capabilities involving the knowledge of all elements using the ontology. This will result in improved autonomy of autonomous systems. The autonomy will have considerable impact on how robots interact with humans. As a result, the use of robots will further benefit our society. Many tedious tasks that currently can only be performed by humans will be performed by robots, which will further improve the quality of life. To the best of the authors'knowledge, AuR is the first group that adopts a systematic approach to develop ontologies consisting of specific concepts and axioms that are commonly used in autonomous robots.

Emerald Group Publishing Ltd2016

Requirements for building an ontology for autonomous robots

Howard Li, Kamilo Andres Melo Becerra

Emerald Group Publishing Ltd2016

Functional and Adaptive Construction for Rescue

Hadi Ardiny

EPFL2017

Functional and Adaptive Construction for Rescue

Requirements for building an ontology for autonomous robots

Spokeheel: Autonomous robot with high mobility and magnetic adhesion.

Requirements for building an ontology for autonomous robots

Spokeheel: Autonomous robot with high mobility and magnetic adhesion.

Functional and Adaptive Construction for Rescue