Integrating planning and execution for ROS enabled service robots using hierarchical action representations

Abstract-The aim of the RoboEarth project is to develop a globally accessible database, that enables service robots to share reusable information relevant to the execution of their daily tasks. Examples of this information are the hierarchical task descriptions, or action recipes, that represent typical household tasks as symbolic action sequences. By annotating these static action representations with hierarchical planner predicates, they can be interpreted by the Hierarchical Task Network planner SHOP2 to compose more flexible, optimized robot plans, based on the actual state of the environment and the available capabilities of the robot. To subsequently execute the composed plans in a typical household environment, the CRAM executive toolbox is adopted, allowing a tight integration between plan execution and run-time knowledge inference. This paper presents the integration of these two components into one cohesive planning and execution framework, tailored for the safe execution of abstract tasks in a challenging household environment. The resulting framework is implemented on the AMIGO service robot and a basic experiment is conducted to demonstrate the frameworks integral functionality

RoboPlanner: Towards an Autonomous Robotic Action Planning Framework for Industry 4.0

Autonomous robots are being increasingly integrated into manufacturing, supply chain and retail industries due to the twin advantages of improved throughput and adaptivity. In order to handle complex Industry 4.0 tasks, the autonomous robots require robust action plans, that can self-adapt to runtime changes. A further requirement is efficient implementation of knowledge bases, that may be queried during planning and execution. In this paper, we propose RoboPlanner, a framework to generate action plans in autonomous robots. In RoboPlanner, we model the knowledge of world models, robotic capabilities and task templates using knowledge property graphs and graph databases. Design time queries and robotic perception are used to enable intelligent action planning. At runtime, integrity constraints on world model observations are used to update knowledge bases. We demonstrate these solutions on autonomous picker robots deployed in Industry 4.0 warehouses

Approaches for action sequence representation in robotics: a review

Robust representation of actions and its sequences for complex robotic tasks would transform robot’s understand- ing to execute robotic tasks efficiently. The challenge is to under- stand action sequences for highly unstructured environments and to represent and construct action and action sequences. In this manuscript, we present a review of literature dealing with representation of action and action sequences for robot task planning and execution. The methodological review was conducted using Google Scholar and IEEE Xplore, searching the specific keywords. This manuscript gives an overview of current approaches for representing action sequences in robotics. We propose a classification of different methodologies used for action sequences representation and describe the most important aspects of the reviewed publications. This review allows the reader to understand several options that do exist in the research community, to represent and deploy such action representations in real robots

Approaches for action sequence representation in robotics: a review

Robust representation of actions and its sequences for complex robotic tasks would transform robot’s understand- ing to execute robotic tasks efficiently. The challenge is to under- stand action sequences for highly unstructured environments and to represent and construct action and action sequences. In this manuscript, we present a review of literature dealing with representation of action and action sequences for robot task planning and execution. The methodological review was conducted using Google Scholar and IEEE Xplore, searching the specific keywords. This manuscript gives an overview of current approaches for representing action sequences in robotics. We propose a classification of different methodologies used for action sequences representation and describe the most important aspects of the reviewed publications. This review allows the reader to understand several options that do exist in the research community, to represent and deploy such action representations in real robots

Logic programming for deliberative robotic task planning

Over the last decade, the use of robots in production and daily life has increased. With increasingly complex tasks and interaction in different environments including humans, robots are required a higher level of autonomy for efficient deliberation. Task planning is a key element of deliberation. It combines elementary operations into a structured plan to satisfy a prescribed goal, given specifications on the robot and the environment. In this manuscript, we present a survey on recent advances in the application of logic programming to the problem of task planning. Logic programming offers several advantages compared to other approaches, including greater expressivity and interpretability which may aid in the development of safe and reliable robots. We analyze different planners and their suitability for specific robotic applications, based on expressivity in domain representation, computational efficiency and software implementation. In this way, we support the robotic designer in choosing the best tool for his application

A review and comparison of ontology-based approaches to robot autonomy

Within the next decades, robots will need to be able to execute a large variety of tasks autonomously in a large variety of environments. To relax the resulting programming effort, a knowledge-enabled approach to robot programming can be adopted to organize information in re-usable knowledge pieces. However, for the ease of reuse, there needs to be an agreement on the meaning of terms. A common approach is to represent these terms using ontology languages that conceptualize the respective domain. In this work, we will review projects that use ontologies to support robot autonomy. We will systematically search for projects that fulfill a set of inclusion criteria and compare them with each other with respect to the scope of their ontology, what types of cognitive capabilities are supported by the use of ontologies, and which is their application domain.Peer ReviewedPostprint (author's final draft

Service-oriented agent architecture for autonomous maritime vehicles

Advanced ocean systems are increasing their capabilities and the degree of autonomy more and more in order to perform more sophisticated maritime missions. Remotely operated vehicles are no longer cost-effective since they are limited by economic support costs, and the presence and skills of the human operator. Alternatively, autonomous surface and underwater vehicles have the potential to operate with greatly reduced overhead costs and level of operator intervention. This Thesis proposes an Intelligent Control Architecture (ICA) to enable multiple collaborating marine vehicles to autonomously carry out underwater intervention missions. The ICA is generic in nature but aimed at a case study where a marine surface craft and an underwater vehicle are required to work cooperatively. They are capable of cooperating autonomously towards the execution of complex activities since they have different but complementary capabilities. The architectural foundation to achieve the ICA lays on the flexibility of service-oriented computing and agent technology. An ontological database captures the operator skills, platform capabilities and, changes in the environment. The information captured, stored as knowledge, enables reasoning agents to plan missions based on the current situation. The ICA implementation is verified in simulation, and validated in trials by means of a team of autonomous marine robots. This Thesis also presents architectural details and evaluation scenarios of the ICA, results of simulations and trials from different maritime operations, and future research directions

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible