37,817 research outputs found
Narrative based Postdictive Reasoning for Cognitive Robotics
Making sense of incomplete and conflicting narrative knowledge in the
presence of abnormalities, unobservable processes, and other real world
considerations is a challenge and crucial requirement for cognitive robotics
systems. An added challenge, even when suitably specialised action languages
and reasoning systems exist, is practical integration and application within
large-scale robot control frameworks.
In the backdrop of an autonomous wheelchair robot control task, we report on
application-driven work to realise postdiction triggered abnormality detection
and re-planning for real-time robot control: (a) Narrative-based knowledge
about the environment is obtained via a larger smart environment framework; and
(b) abnormalities are postdicted from stable-models of an answer-set program
corresponding to the robot's epistemic model. The overall reasoning is
performed in the context of an approximate epistemic action theory based
planner implemented via a translation to answer-set programming.Comment: Commonsense Reasoning Symposium, Ayia Napa, Cyprus, 201
Abstractions and sensor design in partial-information, reactive controller synthesis
Automated synthesis of reactive control protocols from temporal logic
specifications has recently attracted considerable attention in various
applications in, for example, robotic motion planning, network management, and
hardware design. An implicit and often unrealistic assumption in this past work
is the availability of complete and precise sensing information during the
execution of the controllers. In this paper, we use an abstraction procedure
for systems with partial observation and propose a formalism to investigate
effects of limitations in sensing. The abstraction procedure enables the
existing synthesis methods with partial observation to be applicable and
efficient for systems with infinite (or finite but large number of) states.
This formalism enables us to systematically discover sensing modalities
necessary in order to render the underlying synthesis problems feasible. We use
counterexamples, which witness unrealizability potentially due to the
limitations in sensing and the coarseness in the abstract system, and
interpolation-based techniques to refine the model and the sensing modalities,
i.e., to identify new sensors to be included, in such synthesis problems. We
demonstrate the method on examples from robotic motion planning.Comment: 9 pages, 4 figures, Accepted at American Control Conference 201
Robust Decentralized Abstractions for Multiple Mobile Manipulators
This paper addresses the problem of decentralized abstractions for multiple
mobile manipulators with 2nd order dynamics. In particular, we propose
decentralized controllers for the navigation of each agent among predefined
regions of interest in the workspace, while guaranteeing at the same time
inter-agent collision avoidance and connectivity maintenance for a subset of
initially connected agents. In that way, the motion of the coupled multi-agent
system is abstracted into multiple finite transition systems for each agent,
which are then suitable for the application of temporal logic-based high level
plans. The proposed methodology is decentralized, since each agent uses local
information based on limited sensing capabilities. Finally, simulation studies
verify the validity of the approach.Comment: Accepted for publication in the IEEE Conference on Decision and
Control, Melbourne, Australia, 201
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
Quadrotor control for persistent surveillance of dynamic environments
Thesis (M.S.)--Boston UniversityThe last decade has witnessed many advances in the field of small scale unmanned aerial vehicles (UAVs). In particular, the quadrotor has attracted significant attention. Due to its ability to perform vertical takeoff and landing, and to operate in cluttered spaces, the quadrotor is utilized in numerous practical applications, such as reconnaissance and information gathering in unsafe or otherwise unreachable environments.
This work considers the application of aerial surveillance over a city-like environment. The thesis presents a framework for automatic deployment of quadrotors to monitor and react to dynamically changing events. The framework has a hierarchical structure. At the top level, the UAVs perform complex behaviors that satisfy high- level mission specifications. At the bottom level, low-level controllers drive actuators on vehicles to perform the desired maneuvers.
In parallel with the development of controllers, this work covers the implementation of the system into an experimental testbed. The testbed emulates a city using physical objects to represent static features and projectors to display dynamic events occurring on the ground as seen by an aerial vehicle. The experimental platform features a motion capture system that provides position data for UAVs and physical features of the environment, allowing for precise, closed-loop control of the vehicles. Experimental runs in the testbed are used to validate the effectiveness of the developed control strategies
Sustaining entrepreneurial business: a complexity perspective on processes that produce emergent practice
This article examines the management practices in an entrepreneurial small firm which sustain the business. Using a longitudinal qualitative case study, four general processes are identified (experimentation, reflexivity, organising and sensing), that together provide a mechanism to sustain the enterprise. The analysis draws on concepts from entrepreneurship and complexity science. We suggest that an entrepreneur’s awareness of the role of these parallel processes will facilitate their approaches to sustaining and developing enterprises. We also suggest that these processes operate in parallel at multiple levels, including the self, the business and inter-firm networks. This finding contributes to a general theory of entrepreneurship. A number of areas for further research are discussed arising from this result
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