[Federal Register Volume 85, Number 166 (Wednesday, August 26, 2020)]
[Notices]
[Pages 52604-52606]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2020-18677]


=======================================================================
-----------------------------------------------------------------------

DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Disease Control and Prevention

[60Day-20-20PR; Docket No. CDC-2020-0074]


Proposed Data Collection Submitted for Public Comment and 
Recommendations

AGENCY: Centers for Disease Control and Prevention (CDC), Department of 
Health and Human Services (HHS).

ACTION: Notice with comment period.

-----------------------------------------------------------------------

SUMMARY: The Centers for Disease Control and Prevention (CDC), as part 
of its continuing effort to reduce public burden and maximize the 
utility of government information, invites the general public and other 
Federal agencies the opportunity to comment on a proposed and/or 
continuing information collection, as required by the Paperwork 
Reduction Act of 1995. This notice invites comment on a proposed 
information collection project titled Improving Safety of Human-Robot 
Interaction. The purpose of this data collection is to gather 
experimental information in the CDC Division of Safety Research Virtual 
Reality Laboratory on the effects of robot characteristics (e.g. size, 
movement speed, and movement trajectory) on human behavior, perceived 
safety, mental workload, and trust. This information will be used to 
improve the design and modeling of robots and robot functions to reduce 
human-robot collisions as a result of improved robot

[[Page 52605]]

navigation, reduced human workers' workload, and increased trust.

DATES: CDC must receive written comments on or before October 26, 2020.

ADDRESSES: You may submit comments, identified by Docket No. CDC-2020-
0074 by any of the following methods:
     Federal eRulemaking Portal: Regulations.gov. Follow the 
instructions for submitting comments.
     Mail: Jeffrey M. Zirger, Information Collection Review 
Office, Centers for Disease Control and Prevention, 1600 Clifton Road 
NE, MS-D74, Atlanta, Georgia 30329.
    Instructions: All submissions received must include the agency name 
and Docket Number. CDC will post, without change, all relevant comments 
to Regulations.gov.
    Please note: Submit all comments through the Federal eRulemaking 
portal (regulations.gov) or by U.S. mail to the address listed above.

FOR FURTHER INFORMATION CONTACT: To request more information on the 
proposed project or to obtain a copy of the information collection plan 
and instruments, contact Jeffrey M. Zirger, Information Collection 
Review Office, Centers for Disease Control and Prevention, 1600 Clifton 
Road NE, MS-D74, Atlanta, Georgia 30329; phone: 404-639-7570; Email: 
[email protected].

SUPPLEMENTARY INFORMATION: Under the Paperwork Reduction Act of 1995 
(PRA) (44 U.S.C. 3501-3520), Federal agencies must obtain approval from 
the Office of Management and Budget (OMB) for each collection of 
information they conduct or sponsor. In addition, the PRA also requires 
Federal agencies to provide a 60-day notice in the Federal Register 
concerning each proposed collection of information, including each new 
proposed collection, each proposed extension of existing collection of 
information, and each reinstatement of previously approved information 
collection before submitting the collection to the OMB for approval. To 
comply with this requirement, we are publishing this notice of a 
proposed data collection as described below.
    The OMB is particularly interested in comments that will help:
    1. Evaluate whether the proposed collection of information is 
necessary for the proper performance of the functions of the agency, 
including whether the information will have practical utility;
    2. Evaluate the accuracy of the agency's estimate of the burden of 
the proposed collection of information, including the validity of the 
methodology and assumptions used;
    3. Enhance the quality, utility, and clarity of the information to 
be collected; and
    4. Minimize the burden of the collection of information on those 
who are to respond, including through the use of appropriate automated, 
electronic, mechanical, or other technological collection techniques or 
other forms of information technology, e.g., permitting electronic 
submissions of responses.
    5. Assess information collection costs.

Proposed Project

    Improving Safety of Human-Robot Interaction--NEW--National 
Institute of Occupational Safety and Health (NIOSH), Centers for 
Disease Control and Prevention (CDC).

Background and Brief Description

    The mission of the National Institute for Occupational Safety and 
Health (NIOSH) is to promote safety and health at work for all people 
through research and prevention. NIOSH has initiated a study among 
manufacturing workers to improve safety of workers that work in close 
proximity with robots. Study results will be used to improve safety 
standards and lead to better design guidelines for industrial robots.
    Rapid growth of advanced collaborative and mobile robots warrants 
investigation on safe human-robot interaction for their potential 
injurious energy transmission from a robot to a worker. Traditional 
safety measures for industrial robots, such as protective barriers, are 
no longer valid for the emerging collaborative and mobile robots. 
Physical contacts between human workers and robots are inevitable and 
even desired when they share a common workspace or work directly with 
each other under collaborative operations. Therefore, NIOSH is 
proposing a study to evaluate the effects of different characteristics 
of robots on human behaviors, perceived safety, workload, and trust.
    The study will take advantage of virtual reality technology to 
simulate human-robot interaction during data collection sessions. 
Participants will conduct two related experiments that will involve 
performing simulated warehouse tasks (e.g. loading/unloading boxes from 
shelves) in a virtual reality laboratory. Participants will interact 
with a mobile robot in the first experiment and a collaborative robot 
arm in the second. They will wear glasses that will allow them to see 
virtual 3D images of the robots and other objects in the environment. 
During each experiment task, we will use motion capture technology to 
track the movement and location of the participants and the virtual 
robots. This will allow us to track movement speed and separation 
distance from the virtual robots. After each experiment task, we will 
administer three questionnaires to the participants that will ask them 
about their perceived safety, mental workload, and trust in the robots. 
We will analyze how these measures change based on the virtual robot's 
operating speed, size, and movement trajectory.
    Data collections will occur at the NIOSH facility in Morgantown, 
West Virginia. The target study population will be workers who 
currently work or had worked in the manufacturing industry, with 
varying job experiences. The burden table below accounts for 111 
respondents over a three-year data collection period. Respondents will 
complete all forms only once, besides the Virtual Reality Sickness 
Questionnaire, which will be administered at the beginning and end of 
the data collection, and the three questionnaires (NASA Task Load 
Index, Perceived Safety Questionnaire, and Robot Trust Questionnaire), 
which will be administered after each of the 63 combined experiment 
trials. The total estimated burden hours are 217. There are no costs to 
the respondents other than their time.

                                                            Estimated Annualized Burden Hours
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                                              Average
                                                                                             Number of       Number of      burden per     Total burden
               Type of respondents                               Form name                  respondents    responses per   response  (in    (in hours)
                                                                                                            respondent        hours)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Manufacturing Workers...........................  Simulator Sickness Susceptibility                   37               1            1/60               1
                                                   Questionnaire.
                                                  Consent Form..........................              37               1           10/60               6
                                                  Participant Data Collection Form......              37               1            1/60               1
                                                  Virtual Reality Sickness Questionnaire              37               2            1/60               1

[[Page 52606]]

 
                                                  Robot Experience Questionnaire........              37               1            6/60               4
                                                  Actual Experiment 1--Mobile Robot.....              37               1            1.16              43
                                                  Actual Experiment 2--Collaborative                  37               1            1.16              43
                                                   Robot.
                                                  NASA Task Load Index..................              37              63            1/60              39
                                                  Perceived Safety Questionnaire........              37              63            1/60              39
                                                  Robot Trust Questionnaire.............              37              63            1/60              39
                                                                                         ---------------------------------------------------------------
    Total.......................................  ......................................  ..............  ..............  ..............             217
--------------------------------------------------------------------------------------------------------------------------------------------------------


Jeffrey M. Zirger,
Lead, Information Collection Review Office, Office of Scientific 
Integrity, Office of Science, Centers for Disease Control and 
Prevention.
[FR Doc. 2020-18677 Filed 8-25-20; 8:45 am]
BILLING CODE 4163-18-P