ROBOTICS

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.

This research will examine human behaviors and perceptions of safety, trust, and mental workload, while interacting with mobile robots with varying characteristics such as size, speed, and movement path. Findings from this research will provide robot manufacturers with guidelines for designing robots to reduce human-robot collisions because of improved robot navigation, reduced human workers’ workload, and increased trust.

Project Period: 10/01/2022 – 9/30/2026
NIOSH Division: Division of Safety Research
NIOSH Strategic Goal: Improve workplace safety to reduce traumatic injuries.

The use of demolition robots is increasing in the construction sector. Most research has focused on technological advances (e.g., robot sensing and control); however, limited research has specifically addressed the safety of human workers working with demolition robots. This project will investigate causal factors of demolition robot hazards that lead to demolition robot-related traumatic injuries and fatalities among construction workers. Project objectives:

• Identify major hazard sources (e.g., impact, crushing, pinching or pinning of the operator by a robot part)
• Assess machine-related, human-related, and environment-related causal factors of demolition robot hazards
• Provide a base of scientific knowledge for future research, the development of safety controls, and worker training

Project Period: 10/01/2020 – 9/30/2024
NIOSH Division: Division of Safety Research
NIOSH Strategic Goal: Improve workplace safety to reduce traumatic injuries.

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) Program 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 –  09/30/2023
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 –  09/30/2023
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 – 09/30/2023
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 – 09/30/2022
NIOSH Division: Division of Safety Research
NIOSH Strategic Goals: Improve workplace safety to reduce traumatic injuries

Institution: University of Wisconsin-Madison

Abstract: This project investigates the impacts of drone-induced distractions on construction workers at heights. Researchers will test two hypotheses:

1. The drone presence diverts the workers’ visual attention
2. The drone presence requests extra effort from the workers to keep their balance while working on sloped surfaces

To test their hypotheses, researchers will ask construction workers to perform routine jobs under different drone flying conditions. They will measure the workers’ visual attention on the recognition of construction hazards and their efforts to maintain balance. Results will help the occupational safety and health community create guidelines and regulations on the use of drones in construction workplaces and identify policies to control the impact of drone-induced distractions on construction workers.

Project Period: 9/30/2023 – 9/29/2025

Grant Number: 1R21OH012455-01A1

Institution: Missouri University of Science and Technology  Mine Escape Research, Innovation and Technology (MERIT) Center

This initiative brings together researchers from mining and explosives, various engineering fields, and computer and psychological science to advance research initiatives, technological innovations, and interventions in autonomous, robotic, and intelligent (ARI) systems to prevent deaths in the mining industry. For this project, researchers will develop:

• Intelligent data analytics using artificial intelligence (AI) and machine learning algorithms to assure ARI systems
• Cyber and systems network security to secure, protect, and prevent attacks against ARI systems
• An integrated human-centered design and change management system to ensure smooth operations
• An intelligent communication system for bulk data transfer with embedded systems for data warehousing, processing, and usage to provide 360⁰ vision and prevent collisions
• Intelligent robot assistance in mining for safe operations in high-temperature areas, areas with toxic and explosive gasses, or tight spaces for equipment maintenance
• Intelligent mine rescue and post-disaster surveillance for the emerging ARI systems

Project Period: 9/1/2023 – 8/31/2027

Grant number: 1 U60 OH012685-01

Institution: University of Nebraska-Lincoln

Abstract: Construction workers are frequently exposed to fatal hazards in highway work zones.

This project will develop a practical solution that adapts the state-of-the-art sensing and perception technologies into heavy construction equipment operating in complex and dynamic work zones.

This approach takes a fundamentally different direction to transform construction equipment into a smart safety-aware robot that can 1) fully perceive the presences and states of various objects during dynamic construction, 2) track and analyze their locations and behaviors, and 3) detect situations that are considered unsafe according to predefined safety rules. To achieve this, researchers will establish comprehensive safety checking rules and develop a Robot Operating System (ROS)-based software program that can generate an accurate 3D representation of the work zone environment from sensor data and detect unsafe situations defined in the safety checking rules.

Project Period: 7/1/2022 – 6/30/2023

National Construction Center Cooperative Agreement U60OH009762

CPWR Small Study Program

Institution: New Mexico Institute of Mining and Technology

Abstract: This research is an interdisciplinary collaboration to improve self-escape and mine rescue through innovative robotic and autonomy solutions. For this project, researchers will design and demonstrate intelligent mine evacuation and mine rescue systems for underground mining applications. Work will include:

• Designing a multi-agent robotic system to assist mine rescuers during rescue missions in underground mines
• Developing algorithms to assist miners to find the safest and fast paths to safety
• Designing a new communication system to optimize locating, tracking, and communicating with trapped miners and provide AI-assisted self-escape when possible
• Creating and delivering technologically driven hybrid training products to improve self-escape and mine rescue that incorporate the tools and strategies developed in this project

The outcomes of the proposed work include adoption of the developed technologies and strategies through collaboration with partner mining operations, and technology developers, new competency-based training products that incorporate project results, as well as publications and patents.

Project Period: 9/1/2021 – 8/31/2025

Grant Number: 1U60OH012351-01

NIH Reporter

Institution: Missouri University of Science and Technology

Abstract: The aim of the program is to advance research, technological interventions, and training programs to equip miners for safe self-escape from underground mine emergencies. Specific objectives include:

• advancing research in underground wireless communication for continuous communication and localization of miners during mine emergencies
• studying human-robot interactions to facilitate miner self-escape
• studying critical ingress/egress mechanisms for built-in-place refuge alternatives (RAs) subjected to explosions
• evaluating lithium-ion battery (LIB) electric vehicles (EVs) fire risks and recommend effective techniques for emergency response and rescue management
• developing and implement training programs to achieve the research aims and objectives

The human factors research will facilitate safe and effective miner self-escape through miner-centered, robot-assisted technology and emergency management practices using subtasks. These tasks include (i) human factors that affect miners’ ability and willingness to deploy robots; (ii) characterize robotic missions from within a mine; (iii) develop and validate miner-centered robotic interfaces; and (iv) tech transfer. The goal is to enhance refuge alternative design with miner-deployed robots.

Project Period: 9/1/2021 – 8/31/2025

Grant number: 1U60OH012350-01

NIH Reporter

Institutions: University of California, San Francisco and Virginia Tech

Abstract: Construction workers are exposed to well-documented risk factors associated with overexertion injuries, including lifting and lowering, carrying, hand tool use, and static non-neutral postures. Exoskeletons augment the wearer’s strength and have an enormous potential to beneficially impact the construction industry. For this study, researchers will obtain input from construction industry stakeholders to better understand their opinions on potential applications, promoters, and barriers to the acceptance; determine the efficacy; and assess the perceived safety, effectiveness, and acceptability of exoskeletons. Researchers will use a mixed-methods approach incorporating interview and survey, laboratory, and field-based studies. The overarching project goal is to provide guidance in the safe and effective adoption and use of exoskeletons in construction.

Project Period: 9/1/2019 – 8/31/2024

Grant Number: U60OH009762-12H

Institution: University of Florida

Abstract: Workers at heights (e.g., roofs, scaffolds, ladders) who are already at a higher risk of death or serious injury from a fall, are exposed to additional risks posed by drones or unmanned aerial vehicles (UAVs). Researchers will evaluate the effects of UAVs on workers at heights and how it impacts their safety. To do this, they will develop a virtual environment and, using wearable sensors, will analyze where the workers’ look and automatic (physiologic) responses while interacting with a UAV. Increased knowledge about human-UAV interaction will help to generate training for workers and UAV operators, improve the design of future UAVs, and develop safety regulations around UAV operation.

Project Period: 1/4/2021 – 1/4/2022

National Construction Center Cooperative Agreement U60OH009762

CPWR Small Study Program

Institution: Oregon State University

Abstract: Unmanned Aerial Systems (UASs), or drones, have great potential to influence construction performance positively in terms of safety, quality, cost, and schedule. The use of UASs can also expose construction workers to new hazards in addition to the possibility of crashes resulting from operator mistakes or mechanical failures. The goals of this study are to 1) identify and summarize the safety risks associated with the use of UASs in construction; 2) propose and validate solutions for mitigating the identified risks, and 3) to develop a practical model to assist construction companies in evaluating and adjusting the effectiveness of their safety control methods with consideration of using UASs. Researchers will use the Delphi process (interactive, structured, and systematic data-collection technique relying on an expert panel) to determine the relative importance of each safety control method and metric that can be used to measure and improve each method. A practical safety control model will be developed based on the input from the expert panel and tested on several construction sites throughout Oregon.

Publication: A Practical Model for Measuring and Mitigating Safety Risks of Using UAS in Construction

Project Period: 8/15/2020 – 8/14/2021
National Construction Center Cooperative Agreement U60OH009762
CPWR Small Study Program

Institution: University of Utah

Abstract: The hot summer months in the Southwest U.S. desert environment provides a challenging and sometimes precarious situation for many residential construction workers and contractors with temperatures reaching 110 degrees and airborne particulates generated by land excavation and building activities. This project involves deploying a small swarm of drones capable of misting water on a residential construction site during the hot and dry summer months in southwest Utah. Researchers will develop and assess the effect of water-dispersing drones on air quality and air temperature at residential construction sites.

The primary goal of this project is to reduce the frequency of occupational disease by respiratory and dermal hazards in construction. The secondary goal is to reduce the likelihood of temperature extreme incidents in construction and develop intervention strategies to protect these workers.

Publication: Nebulizer-Retrofitted Drone Deployment at Residential Construction Sites

Project Period: 6/1/2020 – 5/31/2021
National Construction Center Cooperative Agreement U60OH009762
CPWR Small Study Program

Institution(s): University of Florida, George Mason University, University of Utah

Abstract: The goal of this project was to use Unmanned Aerial Systems (UASs), or drones, as a data collection platform, combining the data with novel computer vision techniques to create an automated fall hazard detection and monitoring system. The specific objective was to investigate the practical implementation of UASs for monitoring guardrails near unprotected edges and openings. To achieve this objective, a real-time video feed of the construction site was collected using an UAS, and then an image-processing algorithm was developed and tested for guardrails detection from true-color images. This project adopted a case study approach to investigate the technical development of the hazard identification system and then its implementation and testing in a high-rise construction project. The outcomes of the research illustrated that the proposed automated fall hazard recognition system could facilitate recognition of guardrails in high-rise construction projects.

Publication: Using Unmanned Aerial Systems for Automated Fall Hazard Monitoring in High-rise Construction Projects

Project period: 8/16/2018 – 8/15/2019
National Construction Center Cooperative Agreement U60OH009762
CPWR Small Study Program

Institution: Western Center for Agricultural Health and Safety-Renewal, University of California-Davis

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 -9/30/2023
Grant Number: 5U54OH007550-19A

Institution: Occupational Safety and Health Education and Research Centers (T42), University of Utah

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 could 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: 5T42OH008414-14A
NIH Reporter

Institution: University of California-Los Angeles

Abstract: This investigated the connection between the permeation parameters from the modified closed loop permeation system with those from the alternative dextrous robot hand whole glove model. 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. 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: 5R01OH009250-03
NIH Reporter

Institution: Colorado School of Mines (CSM)

Abstract: The MineSENTRY project addresses the problem of radio communications in the absence of a fixed infrastructure. Motivated by the idea of networked radios to form a communication chain, researchers investigated the use of autonomous robots to 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 by 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 remote-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.

Project Period: 9/1/2008 – 8/31/2010
Grant Number: 1R01OH009612-01external icon
NIH Reporter

Institution: K and A Wireless, LLC

Abstract: The objective of this Small Business Innovation Research (SBIR) Phase 1 Project was 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 proposed deploying 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. The proposed system will be capable of moving around the scene to ensure that each responder always has access to a communication link. It will enhance the communication capabilities of emergency responders by deploying a temporary communication infrastructure with minimal human participation. Researchers obtained and tested a proof of concept prototype of a mobile system capable of deploying the temporary network infrastructure and designed a multi-robot control approach that optimizes coverage at the scene.

Project Period: 9/1/2011- 5/31/2012
Grant Number: 1R43OH009833-01A1
NIH Reporter