Skip to main content
SpringerLink
Log in

Chapter 5 Robotics as an Enabler of Resiliency to Disasters: Promises and Pitfalls

  • Chapter
  • First Online:
Resilience in the Digital Age

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12660))

Abstract

The Covid-19 pandemic is a reminder that modern society is still susceptible to multiple types of natural or man-made disasters, which motivates the need to improve resiliency through technological advancement. This article focuses on robotics and the role it can play towards providing resiliency to disasters. The progress in this domain brings the promise of effectively deploying robots in response to life-threatening disasters, which includes highly unstructured setups and hazardous spaces inaccessible or harmful to humans. This article discusses the maturity of robotics technology and explores the needed advances that will allow robots to become more capable and robust in disaster response measures. It also explores how robots can help in making human and natural environments preemptively more resilient without compromising long-term prospects for economic development. Despite its promise, there are also concerns that arise from the deployment of robots. Those discussed relate to safety considerations, privacy infringement, cyber-security, and financial aspects, such as the cost of development and maintenance as well as impact on employment.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 49.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 64.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Amazon Robotics. https://www.amazonrobotics.com/#/

  2. Assembly Robots. https://www.robots.com/applications/robotic-assembly

  3. BostonDynamics: ATLAS. https://www.bostondynamics.com/atlas

  4. Built Robotics. https://www.builtrobotics.com/

  5. DroneDeploy: Drones in Agriculture, Then and Now. https://medium.com/aerial-acuity/drones-in-agriculture-then-and-now-ebde3df01667

  6. Euronews: Farmers use drones to fight drought. https://www.euronews.com/2016/09/12/farmers-use-drones-to-fight-drought

  7. GeekPlus Robotics. https://www.geekplus.com/

  8. Insight Robotics. https://www.insightrobotics.com/en/

  9. Occupational Safety and Health Administration: Robot-related Accident. https://www.osha.gov/

  10. RDI Technologies. https://rditechnologies.com/

  11. Wiki: Hurricane Rita. https://en.wikipedia.org/wiki/Hurricane_Rita

  12. Wiki: Technology readiness level. https://en.wikipedia.org/wiki/Technology_readiness_level

  13. World Disasters Timeline. http://www.mapreport.com/disasters.html

  14. BBC News: Robotic surgery linked to 144 deaths in the US (2015). https://www.bbc.com/news/technology-33609495

  15. Two Billion People Hit by Natural Disasters in the Past Decade (2018). https://www.securitymagazine.com/articles/89535-two-billion-people-hit-by-natural-disasters-in-the-past-decade

  16. Robots’ to replace up to 20 million factory jobs’ by 2030 (2019). https://www.bbc.com/news/business-48760799

  17. Self-Driving Cars-facts and Figures (2020). https://www.driverlessguru.com/self-driving-cars-facts-and-figures

  18. (ACLU), A.C.L.U.: Protecting privacy from aerial surveillance: Recommendations for government use of drone aircraft (2011). https://www.aclu.org/files/assets/protectingprivacyfromaerialsurveillance.pdf

  19. Afghah, F., Razi, A., Chakareski, J., Ashdown, J.: Wildfire monitoring in remote areas using autonomous unmanned aerial vehicles. In: IEEE INFOCOM 2019-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 835–840. IEEE (2019)

    Google Scholar 

  20. Afzaal, H., Zafar, N.A.: Robot-based forest fire detection and extinguishing model. In: 2016 2nd International Conference on Robotics and Artificial Intelligence (ICRAI), pp. 112–117. IEEE (2016)

    Google Scholar 

  21. Ahmadi, M., Stone, P.: A multi-robot system for continuous area sweeping tasks. In: Proceedings 2006 IEEE International Conference on Robotics and Automation. ICRA 2006, pp. 1724–1729. IEEE (2006)

    Google Scholar 

  22. Anderson, M.: Surprise! 2020 Is Not the Year for Self-Driving Cars (2020). https://spectrum.ieee.org/transportation/self-driving/surprise-2020-is-not-the-year-for-selfdriving-cars

  23. Army, T.U.: iRobot PackBot (2009). https://commons.wikimedia.org/wiki/File:Flickr_-_The_U.S._Army_-_iRobot_PackBot.jpg

  24. Bao, D.Q., Zelinka, I.: Obstacle avoidance for swarm robot based on self-organizing migrating algorithm. Procedia Comput. Sci. 150, 425–432 (2019)

    Article  Google Scholar 

  25. Becker, R.: Robot squeezes suspected nuclear fuel debris in Fukushima reactor (2019). https://www.theverge.com/2019/2/15/18225233/robot-nuclear-fuel-debris-fukushima-reactor-japan

  26. Bhagavatula, S.: Robots are getting expensive (2019). https://medium.com/datadriveninvestor/automation-is-getting-expensive-1a4656b1bd9a

  27. Bischoff, R., Huggenberger, U., Prassler, E.: Kuka youbot-a mobile manipulator for research and education. In: 2011 IEEE International Conference on Robotics and Automation, pp. 1–4. IEEE (2011)

    Google Scholar 

  28. Bliss, L.: Could Self-Driving Cars Speed Hurricane Evacuations? (2016). https://www.theatlantic.com/technology/archive/2016/10/self-driving-cars-evacuations/504131/

  29. Burke, R.V., et al.: Using robotic telecommunications to triage pediatric disaster victims. J. Pediatr. Surg. 47(1), 221–224 (2012)

    Article  Google Scholar 

  30. Burmeister, S., Holz, M.: Warning method and robot system, US Patent 9,908,244, March 6 2018

    Google Scholar 

  31. Chen, X., Zhang, H., Lu, H., Xiao, J., Qiu, Q., Li, Y.: Robust slam system based on monocular vision and lidar for robotic urban search and rescue. In: 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), pp. 41–47. IEEE (2017)

    Google Scholar 

  32. Coyle, S., Majidi, C., LeDuc, P., Hsia, K.J.: Bio-inspired soft robotics: material selection, actuation, and design. Extrem. Mech. Lett. 22, 51–59 (2018)

    Article  Google Scholar 

  33. Crozier, S.: Forest Fire “Clear Cut” Robot (2008). https://www.yankodesign.com/2008/04/24/forest-fire-clear-cut-robot/

  34. Customs, U., Protection, B.: CBP Officers deploy underwater robot below a ship (2012). https://commons.wikimedia.org/wiki/File:CBP_Officers_deploy_underwater_robot_below_a_ship_(8405583933).jpg

  35. Deierling, K.: The End of Moore’s Law and the Return of Cleverness (2019). https://blog.mellanox.com/2019/08/the-end-of-moores-law-and-the-return-of-cleverness

  36. D’Monte, L.: 5 Robots That May Rescue You From Natural Disasters (2015). https://www.govtech.com/em/safety/5-Robots-That-May-Rescue-You-From-Natural-Disasters.html

  37. Dockterman, E.: Robot Kills Man at Volkswagen Plant (2015). https://time.com/3944181/robot-kills-man-volkswagen-plant/

  38. Doersch, C., Zisserman, A.: Sim2real transfer learning for 3D human pose estimation: motion to the rescue. In: Advances in Neural Information Processing Systems, pp. 12949–12961 (2019)

    Google Scholar 

  39. Dunbabin, M., Grinham, A., Udy, J.: An autonomous surface vehicle for water quality monitoring. In: Australasian Conference on Robotics and Automation (ACRA), pp. 2–4. Citeseer (2009)

    Google Scholar 

  40. Ellekilde, L.P., Petersen, H.G.: Motion planning efficient trajectories for industrial bin-picking. Int. J. Robot. Res. 32(9–10), 991–1004 (2013)

    Article  Google Scholar 

  41. Ess, A., Schindler, K., Leibe, B., Van Gool, L.: Object detection and tracking for autonomous navigation in dynamic environments. Int. J. Robot. Res. 29(14), 1707–1725 (2010)

    Article  Google Scholar 

  42. Fallon, P.J.: Acoustical/optical bin picking system, US Patent 4,985,846, January 15 1991

    Google Scholar 

  43. Feng, S.W., Yu, J.: Optimally guarding perimeters and regions with mobile range sensors. arXiv preprint arXiv:2002.08477 (2020)

  44. Foster, M.E., By, T., Rickert, M., Knoll, A.: Human-robot dialogue for joint construction tasks. In: Proceedings of the 8th International Conference on Multimodal Interfaces, pp. 68–71 (2006)

    Google Scholar 

  45. Galceran, E., Carreras, M.: A survey on coverage path planning for robotics. Robot. Auton. Syst. 61(12), 1258–1276 (2013)

    Article  Google Scholar 

  46. Garrett, C.R., Huang, Y., Lozano-Pérez, T., Mueller, C.T.: Scalable and probabilistically complete planning for robotic spatial extrusion. arXiv preprint arXiv:2002.02360 (2020)

  47. Gonzalez, C.: Changing the Future of Warehouses with Amazon Robots (2017). https://www.machinedesign.com/mechanical-motion-systems/article/21835788/changing-the-future-of-warehouses-with-amazon-robots

  48. González-Jiménez, H.: Can robots help us overcome the coronavirus health crisis and lockdown? (2020). https://theconversation.com/can-robots-help-us-overcome-the-coronavirus-health-crisis-and-lockdown-134161

  49. Gow, G.: COVID-19 and unemployment: the robots are coming (2020). https://www.forbes.com/sites/glenngow/2020/07/07/covid-19-and-unemployment-the-robots-are-coming/?sh=225497141fab

  50. Han, S.D., Yu, J.: DDM: fast near-optimal multi-robot path planning using diversified-path and optimal sub-problem solution database heuristics. IEEE Robot. Autom. Lett. 5(2), 1350–1357 (2020)

    Article  Google Scholar 

  51. Hanheide, M., et al.: Robot task planning and explanation in open and uncertain worlds. Artif. Intell. 247, 119–150 (2017)

    Article  MathSciNet  Google Scholar 

  52. Hecht, J.: Self-driving vehicles: many challenges remain for autonomous navigation (2020). https://www.laserfocusworld.com/test-measurement/article/14169619/selfdriving-vehicles-many-challenges-remain-for-autonomous-navigation

  53. Hellström, T.: On the moral responsibility of military robots. Ethics Inf. Technol. 15(2), 99–107 (2013)

    Article  MathSciNet  Google Scholar 

  54. Hereid, A., Cousineau, E.A., Hubicki, C.M., Ames, A.D.: 3D dynamic walking with underactuated humanoid robots: a direct collocation framework for optimizing hybrid zero dynamics. In: 2016 IEEE International Conference on Robotics and Automation (ICRA), pp. 1447–1454. IEEE (2016)

    Google Scholar 

  55. Husseini, T.: From Cherno-bots to Iron Man suits: the development of nuclear waste robotics. https://www.power-technology.com/features/cleaning-up-nuclear-waste-robotics/

  56. Islam, F., Salzman, O., Agraval, A., Likhachev, M.: Provably constant-time planning and re-planning for real-time grasping objects off a conveyor. arXiv preprint arXiv:2003.08517 (2020)

  57. Kapoutsis, A.C., Chatzichristofis, S.A., Kosmatopoulos, E.B.: DARP: divide areas algorithm for optimal multi-robot coverage path planning. J. Intell. Robot. Syst. 86(3–4), 663–680 (2017)

    Article  Google Scholar 

  58. Karaman, S., Frazzoli, E.: Incremental sampling-based algorithms for optimal motion planning. Robot. Sci. Syst. VI 104(2), 267–274 (2010)

    Google Scholar 

  59. Kerzel, M., Strahl, E., Magg, S., Navarro-Guerrero, N., Heinrich, S., Wermter, S.: Nico–neuro-inspired companion: a developmental humanoid robot platform for multimodal interaction. In: 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 113–120. IEEE (2017)

    Google Scholar 

  60. Khalid, M.A.B., Shome, R., Stone, C.M.K.B.M.: That and there: judging the intent of pointing actions with robotic arms (2019)

    Google Scholar 

  61. King, J.E., Haustein, J.A., Srinivasa, S.S., Asfour, T.: Nonprehensile whole arm rearrangement planning on physics manifolds. In: 2015 IEEE International Conference on Robotics and Automation (ICRA), pp. 2508–2515. IEEE (2015)

    Google Scholar 

  62. Koceska, N., Koceski, S., Beomonte Zobel, P., Trajkovik, V., Garcia, N.: A telemedicine robot system for assisted and independent living. Sensors 19(4), 834 (2019)

    Article  Google Scholar 

  63. Kroemer, O., Niekum, S., Konidaris, G.: A review of robot learning for manipulation: challenges, representations, and algorithms. arXiv preprint arXiv:1907.03146 (2019)

  64. Krontiris, A., Bekris, K.E.: Efficiently solving general rearrangement tasks: a fast extension primitive for an incremental sampling-based planner. In: 2016 IEEE International Conference on Robotics and Automation (ICRA), pp. 3924–3931. IEEE (2016)

    Google Scholar 

  65. Kulik, S.D., Shtanko, A.N.: Experiments with neural net object detection system YOLO on small training datasets for intelligent robotics. In: Misyurin, S.Y., Arakelian, V., Avetisyan, A.I. (eds.) Advanced Technologies in Robotics and Intelligent Systems. MMS, vol. 80, pp. 157–162. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-33491-8_19

    Chapter  Google Scholar 

  66. LaMonica, M.: Ocean-faring Robot Cashes in on Offshore Oil and Gas (2013). https://www.technologyreview.com/2013/03/20/253500/ocean-faring-robot-cashes-in-on-offshore-oil-and-gas/

  67. Lavalle, S.M.: Sampling-based motion planning (2006)

    Google Scholar 

  68. Lavine, K.: Take3: Left Hand Robotics creates snow-clearing robot (Video) (2018). https://www.bizjournals.com/denver/news/2018/01/02/take3-left-hand-robotics-creates-snow-clearing.html

  69. Levinson, J., Thrun, S.: Robust vehicle localization in urban environments using probabilistic maps. In: 2010 IEEE International Conference on Robotics and Automation, pp. 4372–4378. IEEE (2010)

    Google Scholar 

  70. Li, X., Guo, D., Yin, H., Wei, G.: Drone-assisted public safety wireless broadband network. In: 2015 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), pp. 323–328. IEEE (2015)

    Google Scholar 

  71. Lopez-Arreguin, A., Montenegro, S.: Towards bio-inspired robots for underground and surface exploration in planetary environments: an overview and novel developments inspired in sand-swimmers. Heliyon 6(6), e04148 (2020)

    Article  Google Scholar 

  72. Lu, Q., Fricke, G.M., Tsuno, T., Moses, M.E.: A bio-inspired transportation network for scalable swarm foraging. In: 2020 IEEE International Conference on Robotics and Automation (ICRA), pp. 6120–6126. IEEE (2020)

    Google Scholar 

  73. Luo, C., Espinosa, A.P., Pranantha, D., De Gloria, A.: Multi-robot search and rescue team. In: 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics, pp. 296–301. IEEE (2011)

    Google Scholar 

  74. Mandloi, A., Jaisingh, H.R., Hazarika, S.M.: Perception based navigation for autonomous ground vehicles. In: Deka, B., Maji, P., Mitra, S., Bhattacharyya, D.K., Bora, P.K., Pal, S.K. (eds.) PReMI 2019. LNCS, vol. 11942, pp. 369–376. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-34872-4_41

    Chapter  Google Scholar 

  75. Manjanna, S., Li, A.Q., Smith, R.N., Rekleitis, I., Dudek, G.: Heterogeneous multi-robot system for exploration and strategic water sampling. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 1–8. IEEE (2018)

    Google Scholar 

  76. Margaret Rouse, I.W.: Telepresence robot. https://searchenterpriseai.techtarget.com/definition/telepresence-robot

  77. Meguro, J.I., Ishikawa, K., Hasizume, T., Takiguchi, J.I., Noda, I., Hatayama, M.: Disaster information collection into geographic information system using rescue robots. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3514–3520. IEEE (2006)

    Google Scholar 

  78. Michael Martinez, P.V., Hannah, J.: CNN: germ-zapping robot Gigi sets its sights on Ebola (2014). https://www.cnn.com/2014/10/16/us/germ-zapping-robot-ebola/index.html

  79. Miller, N.: How factories change production to quickly fight coronavirus (2020). https://www.bbc.com/worklife/article/20200413-how-factories-change-production-to-quickly-fight-coronavirus

  80. Mohney, G.: Long Search for Missing Plane Could Cost ‘Hundreds of Millions of Dollars’ (2014). https://abcnews.go.com/International/long-search-missing-plane-cost-hundreds-millions-dollars/story?id=22899690

  81. NASA: Snakebot (2000). https://www.nasa.gov/centers/ames/news/releases/2000/00images/snakebot/snakebot.html

  82. Nayyar, M., Wagner, A.R.: Effective robot evacuation strategies in emergencies. In: 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 1–6. IEEE (2019)

    Google Scholar 

  83. Noha, S.Y., et al.: Design of a 2dofs pantograph leg mechanism for rapid response robot platform in nuclear power plant facilities (2020)

    Google Scholar 

  84. Onosato, M., et al.: Disaster information gathering aerial robot systems. In: Rescue Robotics, pp. 33–55. Springer (2009). https://doi.org/10.1007/978-1-84882-474-4_3

  85. Palmer, A.: Amazon wins FAA approval for Prime Air drone delivery fleet (2020). https://www.cnbc.com/2020/08/31/amazon-prime-now-drone-delivery-fleet-gets-faa-approval.html

  86. Pan, Q., Lowe, D.: Search and rescue robot team RF communication via power cable transmission line-a proposal. In: 2007 International Symposium on Signals, Systems and Electronics, pp. 287–290. IEEE (2007)

    Google Scholar 

  87. Panagou, D.: Motion planning and collision avoidance using navigation vector fields. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 2513–2518. IEEE (2014)

    Google Scholar 

  88. Paraskevas, A., Arendell, B.: A strategic framework for terrorism prevention and mitigation in tourism destinations. Tourism Manag. 28(6), 1560–1573 (2007)

    Article  Google Scholar 

  89. Paul, M.: Don’t Fear the Robots: Why Automation Doesn’t Mean the End of Work (2018). https://rooseveltinstitute.org/publications/dont-fear-the-robots-automation-doesnt-mean-the-end-of-work/

  90. Pierson, A., Schwager, M.: Bio-inspired non-cooperative multi-robot herding. In: ICRA, pp. 1843–1849. Citeseer (2015)

    Google Scholar 

  91. Quaritsch, M., Kuschnig, R., Hellwagner, H., Rinner, B., Adria, A., Klagenfurt, U.: Fast aerial image acquisition and mosaicking for emergency response operations by collaborative UAVs. In: ISCRAM (2011)

    Google Scholar 

  92. Ramirez, V.B.: Waymo Just Started Testing Its Driverless Trucks in Texas (2020). https://singularityhub.com/2020/08/27/waymo-just-started-testing-its-driverless-trucks-in-texas/

  93. Reich, J., Sklar, E.: Robot-sensor networks for search and rescue. In: IEEE International Workshop on Safety, Security and Rescue Robotics, vol. 22 (2006)

    Google Scholar 

  94. Reise, R.: POK Jupiter firefighting robot (2019). https://commons.wikimedia.org/wiki/File:POK_Jupiter_firefighting_robot_(3).jpg

  95. Sadigh, D., Sastry, S., Seshia, S.A., Dragan, A.D.: Planning for autonomous cars that leverage effects on human actions. In: Robotics: Science and Systems, vol. 2. Ann Arbor (2016)

    Google Scholar 

  96. Semuels, A.: Millions of Americans Have Lost Jobs in the Pandemic – and Robots and AI are Replacing them Faster than Ever (2020). https://time.com/5876604/machines-jobs-coronavirus

  97. Shaw, K.: World Robotics Report: Global Sales of Robots Hit \$16.5B in 2018 (2019). https://www.roboticsbusinessreview.com/research/world-robotics-report-global-sales-of-robots-hit-16-5b-in-2018/

  98. Shi, S., Wu, H., Song, Y., Handroos, H.: Mechanical design and error prediction of a flexible manipulator system applied in nuclear fusion environment. Ind. Robot: Int. J. 44(6), 711–719 (2017)

    Google Scholar 

  99. Shome, R., Nakhimovich, D., Bekris, K.E.: Pushing the boundaries of asymptotic optimality in integrated task and motion planning. In: The 14th International Workshop on the Algorithmic Foundations of Robotics (2020)

    Google Scholar 

  100. Shome, R., et al.: Towards robust product packing with a minimalistic end-effector. In: 2019 International Conference on Robotics and Automation (ICRA), pp. 9007–9013. IEEE (2019)

    Google Scholar 

  101. Simoni, M.D., Kutanoglu, E., Claudel, C.G.: Optimization and analysis of a robot-assisted last mile delivery system. Transp. Res. Part E: Logistics Transp. Rev. 142, 102049 (2020)

    Article  Google Scholar 

  102. Ruiz-del Solar, J., Loncomilla, P., Soto, N.: A survey on deep learning methods for robot vision. arXiv preprint arXiv:1803.10862 (2018)

  103. Srivastava, S., Fang, E., Riano, L., Chitnis, R., Russell, S., Abbeel, P.: Combined task and motion planning through an extensible planner-independent interface layer. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 639–646. IEEE (2014)

    Google Scholar 

  104. Strisciuglio, N., et al.: Trimbot 2020: an outdoor robot for automatic gardening. In: ISR 2018 50th International Symposium on Robotics, pp. 1–6. VDE (2018)

    Google Scholar 

  105. Stuart, H., Wang, S., Khatib, O., Cutkosky, M.R.: The ocean one hands: an adaptive design for robust marine manipulation. Int. J. Robot. Res. 36(2), 150–166 (2017)

    Article  Google Scholar 

  106. Sun, P., et al.: Scalability in perception for autonomous driving: Waymo open dataset. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 2446–2454 (2020)

    Google Scholar 

  107. Sutter, J.D.: MIT unveils swimming, oil-cleaning robots (2010). http://edition.cnn.com/2010/TECH/innovation/08/26/mit.oil.robot/index.html

  108. Tanimoto, T., Shinohara, K., Yoshinada, H.: Research on effective teleoperation of construction machinery fusing manual and automatic operation. ROBOMECH J. 4(1), 14 (2017)

    Article  Google Scholar 

  109. Team, R.O.M.: Food Delivery Robots Take to the Streets (2019). https://www.robotics.org/blog-article.cfm/Food-Delivery-Robots-Take-to-the-Streets/212

  110. Tuna, G., Gulez, K., Gungor, V.C.: Communication related design considerations of WSN-aided multi-robot slam. In: 2011 IEEE International Conference on Mechatronics, pp. 493–498. IEEE (2011)

    Google Scholar 

  111. Wakabayashi, D.: Self-Driving Uber Car Kills Pedestrian in Arizona, Where Robots Roam (2018). https://www.nytimes.com/2018/03/19/technology/uber-driverless-fatality.html

  112. Walker, J.: Military Robotics Innovation - Comparing the US to Other Major Powers (2019). https://emerj.com/ai-sector-overviews/military-robotics-innovation/

  113. Wang, H., Zhang, C., Song, Y., Pang, B.: Master-followed multiple robots cooperation slam adapted to search and rescue environment. Int. J. Control. Autom. Syst. 16(6), 2593–2608 (2018)

    Article  Google Scholar 

  114. Wang, R., Mitash, C., Lu, S., Boehm, D., Bekris, K.E.: Safe and effective picking paths in clutter given discrete distributions of object poses. arXiv preprint arXiv:2008.04465 (2020)

  115. Wang, Y., Jordan, C.S., Hanrahan, K., Sanchez, D.S., Pinter, M.: Telepresence robot with a camera boom, US Patent 8,996,165, March 31 2015

    Google Scholar 

  116. Winder, D.: Is the future of cyber crime a nightmare scenario (2016). https://www.raconteur.net/is-future-cyber-crime-a-nightmare-scenario/

  117. Wood, L.J., Zaraki, A., Walters, M.L., Novanda, O., Robins, B., Dautenhahn, K.: The iterative development of the humanoid robot kaspar: an assistive robot for children with autism. In: International Conference on Social Robotics, pp. 53–63. Springer (2017). https://doi.org/10.1007/978-3-319-70022-9_6

  118. Yadron, D., Tynan, D.: Tesla driver dies in first fatal crash while using autopilot mode (2016). https://www.theguardian.com/technology/2016/jun/30/tesla-autopilot-death-self-driving-car-elon-musk

  119. Yamada, T., Ito, T., Ohya, A.: Detection of road surface damage using mobile robot equipped with 2D laser scanner. In: Proceedings of the 2013 IEEE/SICE International Symposium on System Integration, pp. 250–256. IEEE (2013)

    Google Scholar 

  120. Yamamoto, T., Terada, K., Ochiai, A., Saito, F., Asahara, Y., Murase, K.: Development of human support robot as the research platform of a domestic mobile manipulator. ROBOMECH J. 6(1), 4 (2019)

    Article  Google Scholar 

  121. Yan, C., Xiang, X., Wang, C.: Towards real-time path planning through deep reinforcement learning for a UAV in dynamic environments. J. Intell. Robot. Syst. 1–13 (2019)

    Google Scholar 

  122. Yang, G.Z., et al.: Combating Covid-19–the role of robotics in managing public health and infectious diseases (2020)

    Google Scholar 

  123. Yatsuda, A., Haramaki, T., Nishino, H.: A robot gesture framework for watching and alerting the elderly. In: International Conference on Network-Based Information Systems, pp. 132–143. Springer (2018). https://doi.org/10.1007/978-3-319-98530-5_12

  124. Yu, C., et al.: Ds-slam: A semantic visual slam towards dynamic environments. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1168–1174. IEEE (2018)

    Google Scholar 

  125. Yu, J., LaValle, S.M.: Optimal multirobot path planning on graphs: complete algorithms and effective heuristics. IEEE Trans. Robot. 32(5), 1163–1177 (2016)

    Article  Google Scholar 

  126. Yuh, J., Marani, G., Blidberg, D.R.: Applications of marine robotic vehicles. Intell. Serv. Robot. 4(4), 221 (2011)

    Article  Google Scholar 

  127. Zhang, S., Guo, Y.: Distributed multi-robot evacuation incorporating human behavior. Asian J. Control 17(1), 34–44 (2015)

    Article  MathSciNet  Google Scholar 

  128. Zheng, X., Jain, S., Koenig, S., Kempe, D.: Multi-robot forest coverage. In: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3852–3857. IEEE (2005)

    Google Scholar 

  129. Zhou, X.S., Roumeliotis, S.I.: Multi-robot slam with unknown initial correspondence: the robot rendezvous case. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1785–1792. IEEE (2006)

    Google Scholar 

Download references

Acknowledgement

The authors would like to acknowledge the support of the NSF NRT award 2021628 and the NSF HDR TRIPODS 1934924.

Author information

Authors and Affiliations

  1. Rutgers University, New Brunswick, NJ, USA

    Rui Wang, Daniel Nakhimovich, Fred S. Roberts & Kostas E. Bekris

Authors
  1. Rui Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daniel Nakhimovich
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fred S. Roberts
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kostas E. Bekris
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kostas E. Bekris .

Editor information

Editors and Affiliations

  1. DIMACS Center, Rutgers University, Piscataway, NJ, USA

    Fred S. Roberts

  2. Russian Foundation for Basic Research, Moscow, Russia

    Igor A. Sheremet

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Wang, R., Nakhimovich, D., Roberts, F.S., Bekris, K.E. (2021). Chapter 5 Robotics as an Enabler of Resiliency to Disasters: Promises and Pitfalls. In: Roberts, F.S., Sheremet, I.A. (eds) Resilience in the Digital Age. Lecture Notes in Computer Science(), vol 12660. Springer, Cham. https://doi.org/10.1007/978-3-030-70370-7_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-70370-7_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-70369-1

  • Online ISBN: 978-3-030-70370-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation