ROBOTICS

Research

Research Needs

The Center for Occupational Robotics Research has identified the research needs it will address. These research needs are consistent with the robot-related research goals outlined in the NIOSH Strategic Plan: FYs 2019-2023 that are encompassed in three Strategic Goals: 4. Reduce occupational musculoskeletal disorders; 6. Improve workplace safety to reduce traumatic injuries; and, 8. Promote safe and healthy work design and well-being. The research needs align with the four types of research NIOSH conducts: basic/etiologic, intervention, translation, and surveillance. Explore the tabs below to learn more about the research needs the Center will address:

Basic/etiologic research builds a foundation of scientific knowledge on which to base future intervention driven research. Most laboratory and exposure assessment research falls into this category.

Robot-related injuries occur as a result of the complex interactions of multiple risk factors. The primary contributors to the risk of injury are human-related, robot-related, task-related, and environmental.
Basic/Etiologic Research Needs

  1. The identification of human worker risk factors and refinement and development of science-based tolerance or reference values for pain and injury thresholds for human worker contact with robots in the workplace. The factors include:
    • Workers’ cognitive capability
    • Physiological characteristics
    • Biometrics
    • Anthropometry

    These factors may have different implications associated with different types and characteristics of robotics technologies. This line of research also includes:&nbsp:

    • Friction and shear injury thresholds from exoskeleton contact with body regions
    • Joint hyperextension risks associated with wearable robots
  2. The study of human workers’ acceptance and emotional engagement with robots, and its impact on a worker’s health and safety behavior. This research includes evaluating the impact of changes in workers’ attitudes, trust, and perceived safety resulting from various aspects of human-robot interaction such as long-term collaborative relationships.
  3. The measurement of worker’s situational awareness, which refers to an ability to identify, process, and comprehend environmental information, and its impacts on human-robot interactions under normal and abnormal operating conditions. This research includes the evaluation of existing situational awareness research methods and tools for application to varied robotics technologies and work environments.
  4. The study of safe, intuitive, and useful robot technologies and engineering features of collaborative and co-existing robot systems for hazard exposure assessments, field inspections, and incident investigations. Potential technologies and features to be studied include:
    • Enhanced robot sensors
    • Mobility and navigation systems
    • Adaptation and self-learning systems
    • Design and programming of autonomous robots
    • Automation operation assistance systems
    • Cyber-social-physical security
  5. Research on continually changing and advancing complex robot technologies and their impacts on work environments. Technologies include, but are not limited to:
    • Cloud robotics
    • Multi-robot systems
    • Artificial intelligence
    • Deep learning
  6. The study of interface and safety communication features of robots with collaborative functions, powered exoskeletons (i.e. wearable robots), service robots, and other interactive robots that may cause human injuries from sources such as unintended contact, collision, vibration, and overexertion.
  7. The study of industry-specific robot-related health and safety issues. This research includes identification of task-related and environmental based risk factors that are specific to certain industrial sectors that have a high prevalence of robots, such as manufacturing.Additional etiologic research opportunities may be found in industries in which robotics technology is just beginning to be introduced and has high potential for improving workplace safety in sectors such as:
    • Mining
    • Healthcare
    • Services
    • Construction
    • Agriculture
    • Public safety
    • Wholesale
  8. The study of various and dynamic work environments using robot systems. Research is needed to evaluate adaptability of robots to dynamically changing work environments. This line of research focus may include the use of robots in virtual working environments or hazardous situations outside normal operating conditions resulting from robot breakdowns, malfunctions, and unexpected changes in the environment.

Intervention research engages in the development and evaluation of a solution to an occupational safety and health problem or the improvement of an existing intervention.

Intervention is a broad term that includes:

  • Engineering controls
  • Personal protective equipment
  • Emerging wearable technologies for protection (e.g. wearable robotic or passive exoskeleton technologies as a potential form of personal protection by augmenting musculoskeletal capabilities of the user.)
  • Training and information provided to change worker behavior

There are two primary thrusts to this area of occupational robotics research:

  1. Evaluation of robotics technologies as preventive measures for existing workplace hazards.
  2. Development and evaluation of interventions to reduce robot-related injury incidents and improve the safety and well-being of human workers working with robotics technologies.

Intervention Research Needs

  1. The collection and analysis of the differences in fatalities, injuries, and near-miss incidences between workplaces using robotics technologies and similar workplaces without robotics technology.
  2. The evaluation of robotics technologies as potential interventions to reduce or prevent known hazards and the resulting injuries in the workplace. An example of a preventable injury might include a musculoskeletal injury attributed to repetitive lifting.
  3. The development of general and domain-specific metrics for evaluating the safety of robots and human-robot interaction in workplaces.
  4. The evaluation of training that helps workers acquire skills, knowledge, and abilities needed to operate rapidly advancing robots in complex and dynamic industrial environments. This line of research includes:
    • Evaluation of a workers’ learning curve
    • Assessment of the worker skill sets that are necessary to work successfully with or alongside newer and more capable robots
  5. The study of the effectiveness of existing safety standards, certifications, and regulations for industrial robot safety (e.g., ISO/TS 15066, ANSI/RIA R15.06, ISO10218.01, ISO 10218.02, UL1740) in ensuring the safety and well-being of human workers.
  6. Research on new workplace interventions to improve the safety and well-being of human workers working with robotics technologies, including engineering controls and administrative controls. Research may address the costs and benefits of an intervention and its impact on productivity.

Translation research designs and evaluates strategies to translate research findings and theoretical knowledge into practice in the targeted workplace. This type of research seeks to understand why available, effective, evidence-based interventions are not being adopted, and to facilitate the use of existing or newly developed interventions.

Translation Research Needs

  1. Research on aids and barriers to employers using long established safety procedures for protecting workers from traditional industrial robots.
  2. The development and evaluation of plain-language guidance for the prevention of robot-related injuries to workers.
  3. The development and evaluation of dissemination strategies to facilitate the use, by employers and other stakeholders, of existing and new guidance.
  4. The study of the awareness and acceptance of organizations to the use of evidence-based resources to implement robot safety management programs.

Surveillance is a public health term for the ongoing and systematic collection, analysis, and interpretation of data on health outcomes (e.g., injuries and illnesses) and contributors (e.g., behaviors or actions), and the dissemination of these data to those in position to take action. Surveillance research includes development of new methods, tools, and analytic techniques.

Current worker injury data systems do not include detailed information on how a robot-related fatality or injury incident occurred. There is case-based information from investigations of worker injury deaths conducted by NIOSH and the Occupational Safety and Health Administration (OSHA). However, these investigation findings are limited to the traditional industrial robots, and do not address emerging robotics technologies. Additionally, case-based information may not be representative of all robot-related fatalities.

Surveillance Research Needs

  1. The development of surveillance methods and/or analytic techniques to identify and monitor robot-related injury incidents and risk factors, and quantify the burden of occupational injuries using existing data systems.
  2. Case-based investigations of fatalities, injuries and near-miss incidents involving new robotics technologies to understand multi-faceted contributors to each incident.

Current NIOSH Projects

Explore the tabs below to learn more about current NIOSH robotics research projects.

The objective of this project is to conduct a systematic review of case studies of robotic-related equipment that was purchased through the Ohio Bureau of Workers’ Compensation Safety Intervention Grant (SIG) Programexternal icon to prevent workplace injury in the manufacturing sector. NIOSH researchers will conduct a review that will assess if the robot-related interventions implemented through the grant program were effective. Evidence for success will be based on workers’ compensation claims experiences, a reduction in risk factors and safety hazards, acceptance and adoption of the robotic equipment by employees, and the impact of the intervention on productivity and quality of work.

Project Period: 10/01/2018 – 09/30/2021
NIOSH Division: Division of Applied Research Technology
NIOSH Strategic Goals: Reduce occupational musculoskeletal disorders (MSDs); Improve workplace safety to prevent traumatic injuries

This research project will examine human behaviors and performance while interacting with collaborative and mobile robots. NIOSH will conduct a series of research studies that will look at interactions between humans and robots with varying physical characteristics such as size, speed, and trajectory and the effect these characteristics have on safety. Researchers will also explore the effects of different robot-to-human communication methods and messages, for example, messages that are seen, read, spoken, and heard; and messages that are action-based and goal-based. Knowledge gained from this research may improve the safety of manufacturing workers who work in areas shared with robots through enhanced industrial robot design and the development of effective interventions for robot-related safety issues.

Project Period: 10/01/2018 – 09/30/2022
NIOSH Division: Division of Safety Research
NIOSH strategic goal: Improve workplace safety to prevent traumatic injuries

This project seeks to answer basic questions related to automation for heavy vehicles— trucks that exceed 33,000 lbs. such as tractor trailers. Using a driving simulator, NIOSH researchers will collect data on driver performance and skill under different conditions. The purpose is twofold. First, this study will provide information on the minimum time needed for a truck driver to obtain situational awareness when transferring control from an automated mode to a manual mode under varying conditions. Second, the study will evaluate the effects of various levels of automation on driver and road safety. This includes situational awareness, challenges in the transfer of operational control, risk of distraction, and risk of collision. This information will provide valuable information to vehicle designers and will help define sensing criteria for automation sensors and communication between the driver and the computer, such as when the automated system should issue a warning for a driver to take over control of the truck.

Project Period: 10/01/2018 – 09/30/2022
NIOSH Division: Division of Safety Research
NIOSH strategic goal: Improve workplace safety to prevent traumatic injuries

NIOSH is also studying robotics technologies in mining that seeks to keep workers safe on the job.  A brief description of our research is provided below.

  • Mine Rescue Support Machine: Developing a machine to support rescue team safety during the response to catastrophic events
  • Sensor Technologies: Studying sensor technologies that lend to automation and the relocation of workers from work hazards
  • Proximity Detection Systems: Developing guidelines for use in the design and implementation of proximity technology for mobile haulage equipment in underground mining
  • Exoskeletons in Mining: Investigating exoskeletons to reduce manual materials handling injuries

Prevention of Manual Materials Handling Injuries in Mining.
This research project aims to reduce manual material handling injuries in mining by increasing the use of materials handling solutions and safe practices. One approach NIOSH researchers will investigate is the use of exoskeletons to reduce shoulder overexertion injuries for mining tasks. To do this, researchers will analyze mining injury data to determine which manual material handling tasks are associated with shoulder overexertion injuries and determine the physical requirements of these manual material handling tasks. Researchers will choose an exoskeleton to reduce the physical requirements of the tasks on the worker, and study mine workers who are wearing the exoskeleton to better understand if using an exoskeletons is a practical solution for reducing shoulder overexertion injuries during manual material handling.

Project Period: 10/01/2018 – 9/30/2022
NIOSH Division: Pittsburgh Mining Research Division
NIOSH strategic goals: Reduce occupational musculoskeletal disorders (MSDs); Improve workplace safety to prevent traumatic injuries

Unmanned aerial vehicles, or drones, are increasingly used on construction sites and could help reduce construction-related injury and death from hazards such as falls and toxic chemical exposures. At the same time, a drone flying near a worker may also pose a threat to workers from distraction and struck-by incidents. Currently, there is little data on distraction and the potential for drones to cause a fall. The objective of this pilot study is to understand if and when a drone has the potential to distract a worker when working at heights, which could in turn lead to imbalance that could cause a fall. To better understand the potential for drone-induced distraction, researchers will place a worker in a virtual reality environment that simulates a construction site. While the workers are completing a simple task, a virtual drone will be introduced. Researchers will continuously measure the worker’s center of pressure—or the forces applied by the foot to the ground—and quantify their ability to maintain balance.

Project Period: 02/07/2019 – 09/30/2020
NIOSH Division: Division of Safety Research
NIOSH Strategic Goals: Improve workplace safety to reduce traumatic injuries

The breakthroughs in the availability of collaborative robots have significantly increased the potential for physical contact, thus risk of injury, between human and robot workers. Robot collision-avoidance operations through engineering algorithms may offer an advanced measure for impact-injury prevention while allowing robots to function at their full operational speed and production capacities. This pilot study aims to develop a “smart path” strategy to avoid unintentional contacts or collisions between human workers and collaborative robots. To do this, researchers will identify motions of a human worker and collaborative robot in a shared workspace, develop synthesized trajectories—smart paths—of a robot in 3D space that avoids unexpected contacts between collaborative robot and human workers in real-time, and evaluate the effectiveness of the smart paths.

Project Period: 02/26/2019 – 09/30/2020
NIOSH Division: Division of Safety Research
NIOSH Strategic Goals: Improve workplace safety to reduce traumatic injuries

The objective of this pilot study is to evaluate the pressure and force limits on the human body during dynamic human-robot contact events. Collaborative robots are designed to safely work alongside humans, but there are still safety and health concerns and questions that are being raised. Despite the maximum permissible power and force limits that can be determined and programmed in to a robot, force and impacts can be added during dynamic contact situations involving moving workers, such as a worker landing on a robot after a trip, slip or fall. The study aims to investigate changes in force impact and pressure on workers during certain dynamic human-robot contact situations that may occur normally in the workplace. This study will lead to a better understanding of the safety risks involved in working alongside collaborative robots and supplement the test methods and limiting factors described in the current ISO/TS 15066 technical specification for collaborative robots.

Project Period: 03/01/2019 – 09/30/2020
NIOSH Division: Division of Safety Research
NIOSH Strategic Goals: Improve workplace safety to reduce traumatic injuries

NIOSH Extramural Projects

Explore the tabs below to learn more about current NIOSH extramural robotics research projects.

Institution: University of California-Davisexternal icon

The overall goal of the Western Center for Agricultural Health and Safety (WCAHS) at UC Davis is to improve the health and safety of farmers, farm family members, and hired farm workers and their families in western agriculture.

Robotics-Related Subproject: Potential Ergonomic Benefits of Personal Collaborative Robots in Strawberry Harvesting.

Subproject Abstract: California is the nation’s leading producer of strawberries, but strawberry harvesting is a very labor-intensive task that results in many workers suffering from musculoskeletal disorders, especially low back disorders (LBDs). The industry needs a means of controlling LBDs among strawberry workers, while maintaining acceptable productivity levels. Recently, the industry has developed various strawberry harvest-aids to increase productivity. These range from commercial 15-person and 5-9 person machines, to research prototypes, such as 2-person harvest machines and single-person programmable collaborative robots. However, there are limited formal ergonomic and biomechanical studies on any of these newly introduced machines to investigate the coupling between harvest efficiency and the effects on the musculoskeletal system. In April 2019, NIOSH featured a presentation on its Expanding Research Partnership Webinar Series that provided an overview of the commercial strawberry harvest aid machines and described current research on the development and evolution of personal collaborative robots and their potential role in reducing LBDs during strawberry harvesting.

Project Period: 9/30/2016 -9/29/2021
Grant Number:
5U54OH007550-19Aexternal icon
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Institution: University of Utahexternal icon

The University of Utah is an Education and Research Center with many goals and objectives. It’s robotics-related project is detailed below.

Robotics-Related Subproject: Probabilistic Posture Modeling Enhances the Ergonomics and Safety of Human-Robot Collaborations.

Subproject Abstract: The way we work and interact with our workplace environment and coworkers is evolving rapidly with new robotics technologies. As a result, ergonomics and human factors must be innovative in order to meet emerging challenges. We can use wearable sensors, robotics and musculoskeletal models to enable greater knowledge of exposure, injury risk and prevention. One significant challenge is defining the postural relationship between humans and robots during human-robot interactions (HRI). In April 2019, NIOSH featured this project on its Expanding Research Partnership Webinar Series. The presentation highlighted examples of human intention recognition and posture modeling during physical HRI. Robots need to be able to learn, predict and recognize a human’s intention to perform a task, often adapting their motion based on the human’s movement. When a human interacts with a haptic device to perform a task, the robot can be used to estimate human posture and move in a way that optimizes ergonomics. Probabilistic modeling and learning algorithms that consider human biomechanics can be used in this area and have the ability to predict human motion in future steps to minimize risk of future musculoskeletal injuries. Collaborative research between the Ergonomics and Safety Lab and the Utah Learning Lab for Manipulation Autonomy (LL4MA) at the University of Utah is defining new methods to use computer science and ergonomics to enhance human safety and efficiency during HRI.

Project Period: 7/01/2018 – 6/30/2023
Grant Number: 5T42OH008414-14Aexternal icon
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Institution: University of California-Los Angelesexternal icon

The specific aims of this project are:

  • To continue developmental work to optimize a robotic hand system relative to accuracy and precision of permeation/penetration of reference chemicals through gloves;
  • To compare the permeation/penetration of the selected compounds through the selected gloves with and without finger movement of the optimized robotic hand, and with and without press-on nails at temperatures of 25, 30, 32, 35, and 40°C; and
  • To determine the mechanism of glove failures.

Significant Findings:

  • Development of a dynamic flow system for whole gloves on a dextrous robotic hand that is capable of continuous or intermittent sampling of water-soluble chemicals that permeate through gloves
  • Development of a whole glove dextrous robotic hand model, nonmoving and clenching, that was compared with the standard ASTM F739-99a permeation closed loop method for four different disposable glove nitrile materials using the nonvolatile solvent cyclohexanol
  • Development of calibrated sensitive instrumentation to test for the presence of microholes
  • Generation of the first porosity data for disposable gloves
  • Measurement of normalized breakthrough times, lag times, steady state permeation rates, and diffusion coefficients of selected chemicals through four different disposable nitrile materials, the results showing that thicker gloves allowed greater protection than the thinnest gloves for a specific chemical
  • Discovery that robotic hand clenching for whole glove permeation causes more permeation and earlier breakthrough for the thinnest glove but not for the thicker gloves. This suggests a necessary balance between worker comfort/capability of manipulating objects and safety considerations
  • The protection afforded by double gloving is more than double relative to both normalized breakthrough time and steady state permeation rate

Translation of Findings:
The findings will be presented at national conferences and submitted for peer-reviewed publication. The research showed that the extra exposures involved in a moving hand occurred mainly for the thinnest glove, and that workers wearing thin gloves need special attention. This needs to be emphasized in workplace safety discussions.

Outcomes/Impact:
The research results will allow as assessment of the exposure potential of worker based on performance-based criteria such as how thin a glove is, the type of glove, and the type of challenge chemical. More work needs to be done to assess the generality of the results to reduce morbidity and exposure potential.

Project Period: 9/1/2009 – 8/31/2013
Grant Number:
5R01OH009250-03external icon
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Institution: Colorado School of Mines (CSM)external icon

During the one-year effort covered by this request, Mine-SENTRY program activities will focus on developing new technology involving the collaborative interaction of robots with wireless networks for establishing and maintaining communication during emergency response, including:

  • Expansion of the existing mote-based sensor and communication SubTerraN network in the CSM-owned Edgar Mine, with associated research activities to develop enhanced protocols and algorithms that facilitate both geo-location of miners and re-configuration during emergencies for facilitating emergency communication.
  • Development of mine-navigable, autonomous robots to be used as movable wireless nodes, with associated research activities aimed at determining algorithms to move the robots to improve reception, to implement tethered exploration, and to act as relays to bridge network gaps.
  • Conversion of a mine-ready “bobcat” into a tele-operated, semi-autonomous rubble-clearing robot, with associated research activities that study shared autonomy (user plus machine) with force feedback and problems in tele-operation over multi-hop, bandwidth-constrained wireless networks.

Project Abstract/Final Report Abstract:

There is a need for reconfigurable communication systems that can be used in underground environments when fixed infrastructure fails. The MineSENTRY project addresses this need, focusing on the problem of radio communications in the absence of a fixed infrastructure. Motivated by the idea of networked radios to form a communication chains, we investigated the use of autonomous robots that can act as a mobile radio node (AMR) for enhancing communication in tunnels.

Researchers proposed a radio signal strength (RSS) based tethering system whereby an AMR attempts to maintain equal RSS between itself and a leader and between itself and a base station. They demonstrated the idea, through a series of experiments, that culminated in an experiment where a remotely controlled Bobcat front-end loader was driven non-line-of-sight video feedback and tele-operation commands transmitted via mobile robots that automatically moved in the mine to ensure the communication link between the operator and the Bobcat.

Results show that it is feasible to send remotely-controlled equipment into a potentially unsafe underground environment with communication links maintained by autonomous mobile robots acting as radio relays. Deploying such a system can enhance the safety of search and rescue workers in an emergency.

Significant Findings:
The highlights and significant findings related to the specific project aims are:

  • The development of mine-navigable, autonomous robots to be used as movable wireless nodes, with associated research activities aimed at determining algorithms to move the robots to improve reception, to implement tethered exploration, and to act as relays to bridge network gaps.
  • Successful demonstration of an autonomous golf cart deployed as a mobile radio relay for the purpose of remote operation of a tele-operated Bobcat.
  • Conversion of a mine-ready “bobcat” into a tele-operated, semi-autonomous rubble-clearing robot, with associated research activities that study shared autonomy (user plus machine) with force feedback and problems in tele-operation over multi-hop, bandwidth-constrained wireless networks.
  • Successful conversion of an off-the-shelf Bobcat for tele-operated use over a non-line-of-sight mesh radio network.

Translation of Findings
For activities such as emergency response and exploration in subterranean spaces, the ability to keep people out of harm’s way is essential. Results show that it is feasible to send remotely-controlled equipment into a potentially unsafe underground environment with communication links maintained by autonomous mobile robots acting as radio relays. Deploying such a system can enhance the safety of search and rescue workers in an emergency. While results cannot be used today in their current form, they can be used to guide commercial development of an industrial-grade system.

Outcomes/Relevance/Impact
Researchers have demonstrated the feasibility of using autonomous mobile robots as mobile radio relays to act as adaptive communication links between an operator and a remotely-operated vehicle in an underground environment.

Project Period: 9/1/2008 – 8/31/2010
Grant Number:
1R01OH009612-01external icon
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Institution: K and A Wireless, LLCexternal icon

The specific aims of this project are:

  • Design the sensing and control system that uses a single communication signal to drive the motion of the robotic access point such that the communication with the emergency responder is maintained.
  • Develop a motion control algorithm capable of maintaining a good communication performance for multiple users in a network based on the quality of multiple communication signals.

Significant Findings:
This is a summary of the findings of work performed under this Small Business Innovation Research (SBIR)external icon Phase 1 Project. The objective of this SBIR is to develop a multi-robot system capable of autonomously deploying and maintaining a portable and temporary communication infrastructure to provide coverage for emergency responders at the scene of an incident. This project proposes to deploy a portable and temporary communication infrastructure at an emergency scene using a group of robots that work in concert to set up network access points to provide coverage to all emergency responders at a scene. This system will be capable of moving around the scene to ensure that each responder has access to a communication link at all times. The proposed system will enhance the communication capabilities of emergency responders by deploying a temporary communication infrastructure with minimal human participation.

The Phase 1 effort that was completed recently proved that the proposed approach is feasible by achieving the following milestones:

  1. Obtained and tested a proof of concept prototype of a mobile system capable of deploy the temporary network infrastructure
  2. Designed a multi-robot control approach that optimizes coverage at the scene
  3. Developed a block diagram for a fully operational system to be developed in Phase 2.

Future work includes:

  1. Developing a full prototype of the robot capable of deploying a communication node while moving around a building according to the received signal.
  2. Integrating multiple robots with the multi-agent control method and a command system and interface completing the development of the proposed concept.
  3. Testing a fully working prototype in a mock scene with real firefighters to obtain field test results of the complete system.

Project Period: 9/1/2011- 5/31/2012
Grant Number:
1R43OH009833-01A1external icon
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Page last reviewed: September 10, 2019