Multi-robot operator control unit

Powell, Darren; Gilbreath, G. A.; Bruch, Michael

doi:10.1117/12.663817

Cited by 13 publications

(9 citation statements)

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“…Much of the focus is on a common controller for multiple, heterogeneous robotic platforms. For example, Space and Naval Warfare Systems Center [16] has developed an unmanned vehicle and operator control interface capable of controlling and monitoring multiple sets of heterogeneous systems. Grocholsky et.…”

Section: Related Workmentioning

confidence: 99%

Towards a distributed, cognitive robotic architecture for autonomous heterogeneous robotic platforms

Lathrop

Korpela

2009

2009 IEEE International Conference on Technologies for Practical Robot Applications

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This paper describes an early phase towards a general, holistic, distributed robotic architecture capable of supporting different domain specific tasks autonomously or semi-autonomously on multiple platforms. Rather than focusing on individual components and algorithms, we take a systems level approach striving for a task-independent architecture. Our ultimate goal is to employ autonomous scouts that augment a military unit with additional reconnaissance and security assets. We envision one solider controlling a mix of three to five ground and aerial robots in contrast to one solider controlling a single robot as realized in currently deployed systems. Such a general robotic architecture may be useful in other domains to include law enforcement, search, and rescue, hospital logistics, and domestic use. To demonstrate interoperability this paper discusses the architectural design and current set of heterogeneous prototypes built with common hardware, software, and a distributed, web-based operator control unit (OCU). We explore future extensions that incorporate a cognitive architecture and work towards the Joint Architecture for Unmanned Systems (JAUS) compliance.

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Section: Related Workmentioning

confidence: 99%

Towards a distributed, cognitive robotic architecture for autonomous heterogeneous robotic platforms

Lathrop

Korpela

2009

2009 IEEE International Conference on Technologies for Practical Robot Applications

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“…Multi-robot OCU (MOCU) is an architecture designed to make it easy to incorporate customized displays and controls for many heterogeneous platforms and missions in a single interface, allowing for simultaneous control of multiple robots [8]. MOCU includes a monitor mode (Figure 2), which is most similar to the work described here.…”

Section: Prior Workmentioning

confidence: 99%

A hands-off, multi-robot display for communicating situation awareness to operators

Crossman¹,

Marinier²,

Olson

2012

2012 International Conference on Collaboration Technologies and Systems (CTS)

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Abstract-In this paper we introduce work toward this goal of enabling an operator to effectively maintain situation awareness over a team of heterogeneous robots. Most existing operator control units (OCUs) are designed for tele-operation of a single robot and require the constant attention of the operator. As the role of robots increase in important fields such as bomb disposal; intelligence, surveillance, and reconnaissance (ISR); and search and rescue it becomes critical to improve this ratio by enabling multiple robots to be monitored and controlled by a single operator. Toward this goal we have developed the Situations, Actions, Goals, and Environment (SAGE) interface, which utilizes numerous techniques for maintaining operator situation awareness by aiding the operator's perception, comprehension, and projection when controlling a team of ground robots. Techniques that we developed include dynamic view control, event detection and prioritization, uncertainty display, view-invariant markers to make state information globally visible, and animations to avoid jarring distractions. SAGE's interface was automated making it completely hands off, thus the operator could save interaction time for critical tasks such robot tasking. SAGE was deployed by Team Michigan as part of its OCU suite in the 2010 MultiAutonomous Ground-robotic International Challenge (MAGIC). Team Michigan won this competition in part because of its innovative OCU designs, including SAGE, that enabled two operators to control 14 robots simultaneously -a 1-to-7 operator to robot ratio, higher than any other team.

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“…The system also supports any JAUS compatible OCU, including MOCU 7 , as well as other proprietary OCU's such as INL's 3D interface 8 and SSC San Diego's ROBART interface.…”

Section: Communicationsmentioning

confidence: 99%

Modular robotic intelligence system based on fuzzy reasoning and state machine sequencing

et al. 2007

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The fusion of multiple behavior commands and sensor data into intelligent and cohesive robotic movement has been the focus of robot research for many years. Sequencing low level behaviors to create high level intelligence has also been researched extensively. Cohesive robotic movement is also dependent on other factors, such as environment, user intent, and perception of the environment. In this paper, a method for managing the complexity derived from the increase in sensors and perceptions is described. Our system uses fuzzy logic and a state machine to fuse multiple behaviors into an optimal response based on the robot's current task. The resulting fused behavior is filtered through fuzzy logic based obstacle avoidance to create safe movement. The system also provides easy integration with any communications protocol, plug-and-play devices, perceptions, and behaviors. Most behaviors and the obstacle avoidance parameters are easily changed through configuration files. Combined with previous work in the area of navigation and localization a very robust autonomy suite is created.Keywords: robotics, autonomy, obstacle avoidance, arbiter, fuzzy logic, state machine BACKGROUNDThe simplest and most basic form of robot control is tele-operation. During tele-operation, the rules for movement and arbitration among system inputs are relatively simple: user input is mapped directly to motor controller output. As robot autonomy increases, the requirements of the system architecture become increasingly complex. For example, in reflexive tele-operation, data from multiple sensors must be arbitrated with user input and combined into an appropriate output 1,2,3 . When moving from tele-operation to reflexive tele-operation, the space of possible inputs increases linearly and is easily handled by conventional programming techniques.However, the addition of new behaviors and technologies under the Robotics Technology Transfer project 4 at SPAWAR Systems Center, San Diego (SSC San Diego) results in a nonlinear explosion of possible variables to arbitrate. Examples of such behaviors include leader-follower, building exploration, and searching for radioactive sources. These high-level behaviors depend on underlying component behaviors, such as obstacle avoidance, and operate concurrently with the autonomy levels described above. Complexity increases because the high-level behaviors also often need to influence the underlying component behaviors. For example, the building exploration behavior requires the robot to avoid obstacles encountered in its path. However, the leader-follower behavior requires the robot to maintain a close proximity to the leader. Clearly the obstacle avoidance in these two cases must operate differently. A robot with multiple levels of autonomy and various high level and low level behaviors must handle a potentially huge number of internal states in order to behave appropriately in any combination of autonomy level and behavior. If not well designed, the addition of just one new behavior can result in...

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Multi-robot operator control unit

Cited by 13 publications

References 0 publications

Towards a distributed, cognitive robotic architecture for autonomous heterogeneous robotic platforms

Towards a distributed, cognitive robotic architecture for autonomous heterogeneous robotic platforms

A hands-off, multi-robot display for communicating situation awareness to operators

Modular robotic intelligence system based on fuzzy reasoning and state machine sequencing

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