Richard J. Norcross

Development of Standard Test Methods for Unmanned and Manned Industrial Vehicles Used Near Humans

The National Institute of Standards and Technology (NIST) has been researching human-robot-vehicle collaborative environments for automated guided vehicles (AGVs) and manned forklifts. Safety of AGVs and manned vehicles with automated functions (e.g., forklifts that slow/stop automatically in hazardous situations) are the focus of the American National Standards Institute/Industrial Truck Safety Development Foundation (ANSI/ITSDF) B56.5 safety standard. Recently, the NIST Mobile Autonomous Vehicle Obstacle Detection/Avoidance (MAVODA) Project began researching test methods to detect humans or other obstacles entering the vehicle’s path. This causes potential safety hazards in manufacturing facilities where both line-of-sight and non-line-of-sight conditions are prevalent. The test methods described in this paper address both of these conditions. These methods will provide the B56.5 committee with the measurement science basis for sensing systems - both non-contact and contact - that may be used in manufacturing facilities.

Cleaning and Deburring Workstation operations manual

Certain commercial equipment is identified in this paper to adequately describe the systems under development. Such identification does not imply recommendation or endorsement by the National Bureau of Standards, nor does it imply that the equipment is the necessarily the best available for the purpose.

Standard test procedures and metrics development for automated guided vehicle safety standards

The National Institute of Standards and Technologys Intelligent Systems Division has been researching automated guided vehicle (AGV) control based on advanced two-dimensional (2D) imaging sensors that detect dynamic, standard test pieces representing humans towards improving AGV safety standards. Experiments and results are presented in this paper showing the measurement of dynamic standard test pieces from an automated guided vehicle as compared to ground truth. The experimental results will be used to develop standard test methods and to recommend improved standard stopping distance exception language to AGV standards.

Integrating occlusion monitoring into human tracking for robot speed and separation monitoring

Collaborative robots are used in close proximity to humans to perform a variety of tasks, while more traditional industrial robots are required to be stopped whenever a human enters their work-volumes. Instead of relying on physical barriers or merely detecting when someone enters the area, the collaborative system must monitor the position of every person who enters the work space in time for the robot to react. The TC 184/SC 2/WG 3 Industrial Safety group within the International Organization for Standard(ISO) is developing the standards to help ensure collaborative robots operate safely. Collaborative robots require sophisticated sensing technologies that must handle dynamic interactions between the robot and the human. One potential safety risk is the occlusion of a safety sensors field of view due to placement of objects or the movement of people in front of a safety sensor. In this situation the robot could shut down as soon as even a single sensor was partially occluded. Unfortunately this could greatly diminish the extent to which the robot could work collaboratively. In this paper we examine how a human tracking system using multiple laser line scanners [3]was adapted to work with a robot Speed and Separation Monitoring (SSM) safety system and further modified to include occlusion monitoring.

Objective test and performance measurement of automotive crash warning systems

The National Institute of Standards and Technology (NIST), under an interagency agreement with the United States Department of Transportation (DOT), is supporting development of objective test and measurement procedures for vehicle-based warning systems intended to warn an inattentive driver of imminent rear-end, road-departure and lane-change crash scenarios. The work includes development of track and on-road test procedures, and development of an independent measurement system, which together provide data for evaluating warning system performance. This paper will provide an overview of DOTs Integrated Vehicle-Based Safety System (IVBSS) program along with a review of the approach for objectively testing and measuring warning system performance.

An Independent Measurement System for Testing Automotive Crash Warning Systems

This report describes the National Institute of Standards and Technologys (NIST) participation in Phase I of the Integrated Vehicle-Based Safety Systems (IVBSS) program, a safety research program sponsored by the U.S. Department of Transportation (U.S. DOT). The goal of this initiative is to determine potential safety benefits and user acceptance of integrated rear-end, lane-change/merge and road departure crash warning systems for light vehicles and heavy commercial trucks. NISTs primary roles in the program included assisting in the development of verification test procedures, the design, construction, and characterization of an independent measurement system, and providing field support for vehicle test activities. The verification tests provide an objective means to evaluate warning system performance in a safe and controlled test-track environment.

Fused quad audio/visual and tracking data collection to enhance mobile robot and operator performance analyses

Collecting accurate, adequate ground truth and experimental data to support technology evaluations is critical in formulating exact and methodical analyses of the systems performance. Personnel at the National Institute of Standards and Technology (NIST), tasked with developing performance measures and standards for both Urban Search and Rescue (US&R) and bomb disposal robots, have been designing advanced ground truth data collection methods to support these efforts. These new techniques fuse multiple real-time streams of video and robot tracking data to facilitate more complete human robot interaction (HRI) analyses following a robots experiences. As a robot maneuvers through a test method, video and audio streams are simultaneously collected and fed into a quad compressor providing real-time display. This fused quad audio/visual data provides a complete picture of what the operators and robots are doing throughout their evaluation to not only enhance HRI analyses, but also provide valuable data that can be used to aid operator training, encourage implementation improvements by highlighting successes and failures to the developers/vendors, and demonstrate capabilities to end-users and buyers. Quad data collection system deployments to support US&R test methods/scenarios at the 2007 Robot Response Evaluation in Disaster City, Texas will be highlighted.