2,825 research outputs found
Challenges in Collaborative HRI for Remote Robot Teams
Collaboration between human supervisors and remote teams of robots is highly
challenging, particularly in high-stakes, distant, hazardous locations, such as
off-shore energy platforms. In order for these teams of robots to truly be
beneficial, they need to be trusted to operate autonomously, performing tasks
such as inspection and emergency response, thus reducing the number of
personnel placed in harm's way. As remote robots are generally trusted less
than robots in close-proximity, we present a solution to instil trust in the
operator through a `mediator robot' that can exhibit social skills, alongside
sophisticated visualisation techniques. In this position paper, we present
general challenges and then take a closer look at one challenge in particular,
discussing an initial study, which investigates the relationship between the
level of control the supervisor hands over to the mediator robot and how this
affects their trust. We show that the supervisor is more likely to have higher
trust overall if their initial experience involves handing over control of the
emergency situation to the robotic assistant. We discuss this result, here, as
well as other challenges and interaction techniques for human-robot
collaboration.Comment: 9 pages. Peer reviewed position paper accepted in the CHI 2019
Workshop: The Challenges of Working on Social Robots that Collaborate with
People (SIRCHI2019), ACM CHI Conference on Human Factors in Computing
Systems, May 2019, Glasgow, U
The design and implementation of a multi-agent architecture to increase coordination efficiency in multi-AUV operations
This research addresses the problem of coordinating multiple autonomous underwater
vehicle (AUV) operations. An intelligent mission executive has been created that uses
multi-agent technology to control and coordinate multiple AUVs in communication
deficient environments. By incorporating real time vehicle prediction, blackboardbased
hierarchical mission plans and mission optimisation in conjunction with a simple
broadcast communication system this system aims to handle the limitations inherent in
underwater operations and intelligently control multiple vehicles. In this research
efficiency is evaluated and then compared to the current state of the art in multiple AUV
control. The research is then validated in real AUV coordination trials.
Results will show that compared to the state of the art the control system developed and
implemented in this research coordinates multiple vehicles more efficiently and is able
to function in a range of poor communication environments. These findings are
supported by in water validation trials with heterogeneous AUVs.
This thesis will first present an in depth state of the art of the related research topics
including multi-agent systems, collaborative robotics and autonomous underwater
vehicles. The development and functionality of this research will then be explained
followed by a detailed description of the experiments. Results are then presented both
for the simulated and real world trials followed by a discussion of the findings
Technical benefits and cultural barriers of networked Autonomous Undersea Vehicles
Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 44-45).The research presented in this thesis examines the technical benefits to using a collaborative network of Autonomous Undersea Vehicles (AUVs) in place of individual vehicles. Benefits could be achieved in the areas of reduced power consumption, improved positional information and improved acoustic communication bandwidth. However, current culture of AUV development may impede this approach. The thesis uses the Object Process Methodology (OPM) and principles of System Architecture to trace the value of an AUV system from the scientist who benefits from the data to the vehicle itself. Sections 3 and 4 outline the needs for an AUV system as they currently exist and describe the key physics-based limitations of operations. Section 5 takes a broader look at the system goal as data delivery, not just the deployment of a vehicle, and introduces the concept of networked AUV. Section 6 describes a potential evolution of networked AUVs in increasing autonomy and collaboration. Finally, Section 7 examines AUV development cultures that could impede, or foster, networked vehicles.by Patrick L. Wineman.S.M
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
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