Requirements for building an ontology for autonomous robots

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.

Enabling Large-Scale Collective Systems in Outdoor Aerial Robotics

Severin Leven

For many real-life applications such as monitoring, mapping, search-and-rescue or ad-hoc communication networks, fleets of flying robots are expected to out-perform existing solutions. Robots can join forces to cover larger areas in less time, act as efficient communication relays and overcome difficult terrain more easily than ground-based robots. Compared to a single robot, the main advantages of collective systems are robustness, parallelism, flexibility, and the fact that they enable tasks that could not be solved by a single robot. While a multitude of theoretical models for collective operation have already been developed and tested in simulation, they have rarely been validated with physical robots yet. Transition to reality has so far been inhibited because of strong limitations in scalability. Indeed, the cost, safety risk, and number of operators associated with a collective aerial system increase proportionally with the number of robots. Substituting such systems for single robots is therefore unattractive or even impracticable. In previous experimental approaches, a maximum of five physical robots were operated simultaneously in outdoor scenarios, assisted by human backup pilots on the ground. In contrast, most theoretical models rely on a minimum of ten robots to obtain interesting swarm effects. With respect to this discrepancy, we consider here ten robots to be a large-scale system in aerial robotics. In order to scale real collective aerial systems to at least ten robots, we suggest the following paradigm: flying robots must be low-cost, inherently safe, deal with mid-air collisions and require minimal supervision from an operator on the ground, such that the entire system warrants similar cost as well as similarly safe and easy deployment as a single, classical flying robot. Moreover, this would make swarms of flying robots as accessible as wheeled robots that have already been used successfully in larger collective systems. The above criteria can best be addressed with a global, systematic approach on all major design levels, which are the robot's airframe, low-level control, collective supervision and control as well as mid-air collision avoidance. On each level, we identified the bottlenecks related to scaling and developed methods for compliant robot design. Based on a systematic analysis of airframe configurations, a flying-wing is proposed that is made of low-cost, safe and durable foam material and can be deployed everywhere by hand-launch. A model for the dimensioning of such an airframe is presented. For low-level control, a novel minimalist control strategy is proposed, implemented on an inexpensive, custom-made autopilot and validated in field tests. In order to enable robots for collective operation, we suggest to use WiFi communication links and embedded Linux-computers onto which swarm designers can download distributed controllers for collective behaviors directly from their computer simulation. Furthermore, the idea is put forward to enable collective supervision through an operator interface with the modality for direct group-control. Implemented and field-proven, these solutions can serve as guidelines for other developers. Finally, the problem that robots may collide with each other during collective operation has been addressed with a model assessing the collision risk and a distributed strategy for mid-air collision avoidance, validated on real robots. Applying the proposed methodology allowed us to demonstrate the world's first collective system composed of ten autonomous flying robots in outdoor experiments with several different collective behaviors. Robots are low-cost (about 1/10 the cost of commercially available robots), inherently safe (kinetic energy of a medium-sized bird) and can be configured, deployed and supervised by a single operator on the ground. This represents a significant step for the scaling of flying collective systems with respect to the state of the art as well as an unprecedented operator-to-robot ratio.

EPFL2011

Control of Contact Tasks in Autonomous and Human-Robot Collaborative Scenarios: A Dynamical System Approach

Walid Amanhoud

Robotic systems are more and more present in our daily life. Robots became indeed more economical, easy to program, safe and collaborative in their interaction with humans, versatile in performing different tasks and adaptive towards changes in the environment. Despite the recent advances in robotics, developingfully autonomous robots to achieve complex industrial or daily-life tasks is still very challenging. The human, due to his superior perception, understanding and reasoning skills, especially in uncertain environment, needs to be in the loop. Therefore, the ability of robots to collaborate with humans is of great interest inthe robotics community. Human-Robot Collaboration usually implies robots that share the control of the tasks with humans, providing adjustable autonomy level and mutual adaptation. A field that can particularly benefits from such collaboration is assistive robotics surgery. The introduction of shared autonomyin surgical tasks has several advantages. In particular, it can provide higher accuracy, flexibility, control and efficiency during the operation, over longer time periods, relieve the surgeon during repetitive tasks and reduce his mental workload. However, it is not very clear how to best use shared control to assist asurgeon during the operation. As part of a research project (the "Surgical project"), in this thesis we would like to propose solutions to that problem by building a teleoperated shared control architecture for a laparoscopic surgery scenario. While laparoscopic surgery usually involves one surgeon and two humanassistants to perform the surgery, the project aims to replace the assistants by two partially teleoperated robotic systems. The target shared control architecture would explore various strategies to ensure safety for both the patient and the surgeon, provide accuracy and stability in motion and force control of the toolsattached to the robots, reduce the mental workload of the surgeon and adapt the level of assistance based on well-identified criteria.The first year was mainly devoted to the control of motion and force for contact tasks which is of great importance in the context of the project. Robot force control is traditionally achieved either explicitly through hybrid position/force control or implicitly using impedance control. We propose an approach leveraging theproperties of dynamical systems (DS) for immediate re-planning and robustness to real-time perturbations by exploiting local modulation of the DS. Dynamical systems has been widely used as a tool to represent and generate motion in robotics application. Here the idea is to propose a DS formulation to generatecontact force in addition to motion. First implementation and experiments to evaluate the effectiveness of the strategy were conducted in practice with a 7-DOF robotic arm (KUKA LWR IV+).So far we focused on contact tasks that were performed autonomously by one or two robots. Future work will improve and use the proposed DS approach to consider contact tasks in shared control scenarios where one human and one or two robots need to collaborate to successfully achieve the tasks. Because of the nature of the surgical project we will use teleoperation systems to introduce the human in the loop. The developed teleoperated shared control architecture will be evaluated on laparoscopic surgery related tasks.

EPFL2021

Cognitive twin construction for system of systems operation based on semantic integration and high-level architecture

Han Li, Jinzhi Lu

With the increasing complexity of engineered systems, digital twins (DTs) have been widely used to support integrated modeling, simulation, and decision-making of the system of systems (SoS). However, when integrating DTs of each constituent system, it is challenging to implement complexity management, interface definition, and service integration across DTs. This study proposes a new concept called cognitive twin (CT) to support SoS development and operation. CTs have been defined as DTs with augmented semantic capabilities for promoting the understanding of interrelationships be-tween virtual models and enhancing the decision-making. First, CTs aim to integrate the information description of DTs across constituent systems using a unified ontology and semantic modeling technique. Second, CTs provide integrated simulations among DTs for decision-making of the SoS based on a high-level architecture (HLA). Finally, through reasoning ontology models, CTs provide decision-making options for the operations of real constituent systems. A case study on unmanned aerial vehicles (UAVs) landing on unmanned surface vehicles (USVs) is used to verify the flexibility of this approach. From the results, we find that the CT based on the proposed ontology provides a unified formalism of DTs across UAVs and USVs. Moreover, the reasoning based on the CT provides decision-making capabilities for UAVs by implementing cognitive computing to select target USVs for landing.