Roger Bostelman

National Institute of Standards and Technology

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Tsai Hong Hong

National Institute of Standards and Technology

James S. Albus

National Institute of Standards and Technology

Tommy Chang

Purdue University West Lafayette

Mili Shah

Brooklyn Hospital Center

Will Shackleford

Intelligent Systems Research (United States)

Ya-Shian Li-Baboud

National Institute of Standards and Technology

Soocheol Yoon

National Institute of Standards

Michael Shneier

National Institute of Standards and Technology

Jeremy A. Marvel

National Institute of Standards

Ann Virts

National Institute of Standards and Technology

Cooperative Institutions

National Institute of Standards and Technology

National Institute of Standards

University of Maryland, College Park

Intelligent Systems Research (United States)

United States Department of Commerce

Florida Gulf Coast University

Obuda University

Purdue University West Lafayette

Harvard University

Cooper Union

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Towards Measurement of Advanced Mobile Manipulator Performance for Assembly Applications

Roger Bostelman Ya-Shian Li-Baboud Soocheol Yoon Mili Shah Omar Aboul-Enein

Advanced mobile manipulators offer the manufacturing industry the potential of a highly adaptive system to perform precision assembly tasks in agile environments.Developing performance measurement capabilities for mobile manipulator systems will support the advancement of manipulator-vehicle coordination, precision, accuracy, and robustness.The National Institute of Standards and Technology (NIST) developed a measurement methodology for advanced mobile manipulators, which are mobile robots with an onboard robot arm, each from a different manufacturer and with a different controller.The measurement methodology is designed to assess the performance of mobile manipulators for manufacturing applications such as assembly, where position and orientation accuracy are critically important.The proposed methodology used an artifact designed at NIST to simulate an assembly task station.An optical tracking system measured the location of the targets, the mobile base position and orientation, and the position of a manipulator end-of-arm tool.The experimental data collected, using three different system computers, were timestamped using local clocks synchronized via the NIST internal and local area networks to align the data streams.The mobile manipulator system, the experimental methodology, the data analysis, and the results of the measurement methodology uncertainty and mobile manipulator positioning uncertainty using the novel artifacts are described in this paper.For the system tested, the mobile manipulator detection of 2 mm diameter fiducials can be achieved after registration.With validation from the optical tracking system, the study demonstrated that the Reconfigurable Mobile Manipulator Artifact (RMMA) has potential for serving as a novel standalone, low-cost test method for measuring the positioning uncertainty of mobile manipulators within a measurement uncertainty of 2 mm.

Manipulator (device)

Mobile manipulator

10.6028/nist.tn.2108

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Citations (4)

Learning in a hierarchical control system: 4D/RCS in the DARPA LAGR program

Journal of Field Robotics (2006)

Jim Albus Roger Bostelman Tommy Chang Tsai Hong Hong Will Shackleford

Abstract The Defense Applied Research Projects Agency (DARPA) Learning Applied to Ground Vehicles (LAGR) program aims to develop algorithms for autonomous vehicle navigation that learn how to operate in complex terrain. Over many years, the National Institute of Standards and Technology (NIST) has developed a reference model control system architecture called 4D/RCS that has been applied to many kinds of robot control, including autonomous vehicle control. For the LAGR program, NIST has embedded learning into a 4D/RCS controller to enable the small robot used in the program to learn to navigate through a range of terrain types. The vehicle learns in several ways. These include learning by example, learning by experience, and learning how to optimize traversal. Learning takes place in the sensory processing, world modeling, and behavior generation parts of the control system. The 4D/RCS architecture is explained in the paper, its application to LAGR is described, and the learning algorithms are discussed. Results are shown of the performance of the NIST control system on independently‐conducted tests. Further work on the system and its learning capabilities is discussed. © 2007 Wiley Periodicals, Inc.

NIST

Unmanned ground vehicle

10.1002/rob.20162

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Citations (23)

Survey of industrial manipulation technologies for autonomous assembly applications

Roger Bostelman Joe Falco

10.6028/nist.ir.7844

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Citations (12)

Experiments toward non-contact safety standards for automated industrial vehicles

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2005)

Roger Bostelman Tsai Hong Hong Raj Madhavan

The performance evaluation of an obstacle detection and segmentation algorithm for Automated Guided Vehicle (AGV) navigation in factory-like environments using a new 3D real-time range camera is the subject of this paper. Our approach expands on the US ASME B56.5 Safety Standard, which now allows for non-contact safety sensors, by performing tests on objects specifically sized in both the US and the British Safety Standards. These successful tests placed the recommended, as well as smaller, material-covered and sized objects on the vehicle path for static measurement. The segmented (mapped) obstacles were then verified in range to the objects and object size using simultaneous, absolute measurements obtained using a relatively accurate 2D scanning laser rangefinder. These 3D range cameras are expected to be relatively inexpensive and used indoors and possibly used outdoors for a vast amount of mobile robot applications building on experimental results explained in this paper.

Factory (object-oriented programming)

10.1117/12.602334

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Citations (3)

Modeling Performance Measurement of Mobile Manipulators

Roger Bostelman Sebti Foufou Tsai Hong Hong

Mobile manipulators are being marketed around the world as single manufacturer systems (i.e., robot arm and vehicle manufactured by the same organization) and as independent robot arms, from a different manufacturer and integrated with automatic guided vehicles (AGVs) or mobile robots. Test methods for measuring safety and performance of either of these types of mobile manipulators have yet to be developed and therefore, potential users cannot compare one system to another to match to tasks. Similarly, the control of these systems can vary greatly from AGV control to more autonomous mobile robot control and further, to robot arm control methods. Systems Modeling Language (SysML) is a general-purpose modeling language for systems engineering applications that supports the specification, analysis, design, verification, and validation of simple through complex systems, such as mobile manipulators. This paper uses SysML to describe a method using an artifact for performance measurement of mobile manipulators performing assembly tasks. Uncertainty propagation, a key component in understanding the effects of mobile manipulator constraints, is also modeled and described.

Artifact (error)

Mobile manipulator

Component (thermodynamics)

10.1109/cyber.2017.8446329

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Citations (2)

Survey of Patient Mobility and Lift Technologies: Toward Advancements and Standards

Roger Bostelman James S. Albus

A two piece incorporated device designed to assist in the lifting and transfer of such person who is partially incapacitated by infirmity or disability from one sitting position in one location to another sitting position in another location. (ex: wheelchair to toilet, bed to chair, etc.) The device includes a torso belt with hold and support handles on back, secured by sewn on hook and loop style fastener; and a thigh support segment with handles sewn into either end, which supports the posterior and weight of said patient. The connection of these two pieces with quick- disconnect buckles provides a greater sense of balance for patient and attendant(s) and helps eliminate weight stress on the patient by virtue of proper weight distribution. The thigh support segment is also equipped with forward positioning straps (at either end), which facilitate a rocking forward by the attendant(s), bringing patient closer prior to lifting. United States Patent 6,637,610 Cheeseboro October 28, 2003 ------------------------------------------------------------------------ Personal transporter Abstract Structure and procedures for lifting, transferring and moving a person, such as a bed ridden person or one requiring the use of a wheelchair, involve a frame (393) supported on wheels (394, 395), a horizontal load supporting beam (392) in an upper part of the frame, and a motor- Structure and procedures for lifting, transferring and moving a person, such as a bed ridden person or one requiring the use of a wheelchair, involve a frame (393) supported on wheels (394, 395), a horizontal load supporting beam (392) in an upper part of the frame, and a motor-

Sitting

Torso

Lift (data mining)

Hook

10.6028/nist.ir.7384

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Citations (18)

Mobile Manipulator Performance Measurement Towards Manufacturing Assembly Tasks

IFIP advances in information and communication technology (2016)

Roger Bostelman Sebti Foufou Steve Legowik Tsai Hong Hong

Mobile manipulator

Artifact (error)

Manipulator (device)

Tracking (education)

10.1007/978-3-319-54660-5_37

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Citations (8)

Performance Analysis of an Autonomous Mobile Robot Mapping System for Outdoor Environments

Roger Bostelman Tao Hong R. Madhavan Tommy Chang Harry A. Scott

As unmanned ground vehicles take on more and more intelligent tasks, determination of potential obstacles and accurate estimation of their position become critical for successful navigation and path planning. The performance analysis of obstacle mapping and unmanned vehicle positioning in outdoor environments is the subject of this paper. Recently, the National Institute of Standards and Technology's (NIST) Intelligent Systems Division has been a part of the Defense Advanced Research Project Agency LAGR (Learning Applied to Ground Robots) Program. NIST's objective for the LAGR Project is to insert learning algorithms into the modules that make up the NIST 4D/RCS (Four Dimensional/Real-Time Control System) standard reference model architecture which has been successfully applied to many intelligent systems. We detail world modeling techniques used in the 4D/RCS architecture and then analyze the high precision maps generated by the vehicle world modeling algorithms as compared to ground truth obtained from an independent differential GPS system operable throughout most of the NIST campus. This work has implications, not only for outdoor vehicles but also, for indoor automated guided vehicles where future systems will have more and more onboard intelligence requiring non-contact sensors to provide accurate vehicle and object positioning

NIST

Unmanned ground vehicle

10.1109/icarcv.2006.345411

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Citations (3)

A-UGV Capabilities - Recommended Guide to Autonomy Levels

Roger Bostelman Elena R. Messina

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Citations (1)

A multipurpose robotic wheelchair and rehabilitation device for the home

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (2007)

Roger Bostelman James S. Albus

This paper describes a novel home lift, position, and rehabilitation (HLPR) chair, designed at National Institute of Standards and Technology (NIST), to provide independent patient mobility for indoor tasks, such as moving to and placing a person on a toilet or bed, and lift assistance for tasks, such as accessing kitchen or other tall shelves. These functionalities are currently out of reach of most wheelchair users. One of the design motivations of the HLPR Chair is to reduce back injury, typically, an important issue in the care of this group. The HLPR Chair is currently being extended to be an autonomous mobility device to assist cognition by route and trajectory planning. This paper describes the design of HLPR Chair, its control architecture, and algorithms for autonomous planning and control using its unique kinematics.

Lift (data mining)

10.1109/iros.2007.4398980

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Citations (23)