Nothing Special   »   [go: up one dir, main page]

Skip to main content

Advertisement

Log in

Quantum robotics: a review of emerging trends

  • Review Article
  • Published:
Quantum Machine Intelligence Aims and scope Submit manuscript

Abstract

Quantum computation and artificial intelligence are separately considered transformative technologies that are shaping our present and future. The prospect of combining the two paradigms portends astounding computing power and human-level intelligence for resulting technologies. One area that seems ripe to reap from this amalgamation is the field of robotics. This could potentially lead to the realization of advanced robots that are controlled using quantum computing resources. Whereas the idea of quantum robots is not new, the advances it has recorded have not been commensurate with the inroads in the two fields separately. Many hold the view that quantum algorithms and notably quantum machine learning will play leading roles in shaping future robotics and automation of integrated systems. Consequently, it is widely anticipated that quantum algorithms, quantum sensors, and quantum controls will be at the fulcrum of next-generation robotics. This study is primarily aimed as an exposition on the advances in the nascent research field of quantum robotics. By summarizing their architectures as well as discussions on their perception and interactions, it is hoped that our effort will stimulate interest leading to innovative ideas to complement current designs and frameworks geared towards realizing the astounding promises of quantum robotics.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Data availability

No datasets were generated or analyzed during the current study.

References

  • Abdor-Sierra JA, Merchán-Cruz EA, Rodríguez-Cañizo RG (2022) A comparative analysis of metaheuristic algorithms for solving the inverse kinematics of robot manipulators. Results Eng 16:100597

    Article  Google Scholar 

  • Abdulridha HM, Hassoun ZA (2018) Control design of robotic manipulator based on quantum neural network. J Dyn Syst Meas Control 140(6):061002

    Article  Google Scholar 

  • Aerts D (2009) Quantum structure in cognition. J Math Psychol 53(5):314–348

    Article  MathSciNet  Google Scholar 

  • Aerts D, Sozzo S, Veloz T (2015) Quantum structure in cognition and the foundations of human reasoning. Int J Theor Phys 54(12):4557–4569

    Article  MathSciNet  Google Scholar 

  • Aerts D, Gabora L, Sozzo S, Veloz T (2011) Quantum structure in cognition: fundamentals and applications. arXiv:1104.3344

  • Antonio C, Salvatore G, Maria M, Giovanni P, Valeria S, Filippo V, Salvatore Z (2023) Quantum planning for swarm robotics. Robot Auton Syst 161:104362

    Article  Google Scholar 

  • Artemov K, Kolyubin S (2020) Design and validation of two-stage motion control system for by-air quantum key distribution. In: 2020 International Conference Nonlinearity, Information and Robotics, pp 1–6

  • Axelrod R, Hamilton WD (1981) The evolution of cooperation. Science 211(4489):1390–1396

    Article  MathSciNet  Google Scholar 

  • Ayyildiz M, Cetinkaya K (2016) Comparison of four different heuristic optimization algorithms for the inverse kinematics solution of a real 4-DOF serial robot manipulator. Neural Comput Appl 27(4):825–836

    Article  Google Scholar 

  • Bahrin MAK, Othman MF, Azli NHN, Talib MF (2016) Industry 4.0: a review on industrial automation and robotic. J Teknol 78:6–13

    Google Scholar 

  • Beer JM, Fisk AD, Rogers WA (2014) Toward a framework for levels of robot autonomy in human-robot interaction. J Hum-robot Interaction 3(2):74

    Article  Google Scholar 

  • Beim Graben P (2004) Incompatible implementations of physical symbol systems. Mind Matter 2(2):29–51

    MathSciNet  Google Scholar 

  • Bellingham JG, Rajan K (2007) Robotics in remote and hostile environments. Science 318(5853):1098–1102

    Article  Google Scholar 

  • Benioff P (1997) Quantum robots and quantum computers. arXiv:quant-ph/9706012

  • Benioff P (1998) Quantum robots and environments. Phys Rev A 58(2):893

    Article  MathSciNet  Google Scholar 

  • Biamonte J, Wittek P, Pancotti N, Rebentrost P, Wiebe N, Lloyd S (2017) Quantum machine learning. Nature 549(7671):195–202

    Article  Google Scholar 

  • Breazeal C, Scassellati B (1999) How to build robots that make friends and influence people. Intell Robot Syst 2:858–863

    Google Scholar 

  • Busemeyer JR, Wang Z (2015) What is quantum cognition, and how is it applied to psychology? Curr Dir Psychol Sci 24(3):163–169

    Article  Google Scholar 

  • Cao Y, Wang W, Ma L, Wang X (2021) Inverse kinematics solution of redundant degree of freedom robot based on improved quantum particle swarm optimization. In: 2021 IEEE international conference on control science and systems engineering, pp 68–72

  • Chella A, Gaglio S, Pilato G, Vella F, Zammuto S (2022) A quantum planner for robot motion. Mathematics 10(14):2475

    Article  Google Scholar 

  • Chella A, Gaglio S, Mannone M, Pilato G, Seidita V, Vella F, Zammuto S (2023) Quantum planning for swarm robotics. Robot Auton Syst 161:104362

    Article  Google Scholar 

  • Chen Y, Chen W (2021) Optimizing the obstacle avoidance trajectory and positioning error of robotic manipulators using multigroup ant colony and quantum behaved particle swarm optimization algorithms. Int J Innov Comput Inf Control 17(2):595–611

    Google Scholar 

  • Chen C, Dong D (2008) A quantum-inspired Q-learning algorithm for indoor robot navigation. In: 2008 IEEE international conference on networking, sensing and control, pp 1599–1603

  • Chen C, Dong D (2012) Quantum parallelization of hierarchical Q-learning for global navigation of mobile robots. In: 2012 IEEE international conference on networking, sensing and control, pp 163–168

  • Clark J, West T, Zammit J, Guo X, Mason L, Russell D (2019) Towards real time multi-robot routing using quantum computing technologies. In: 2019 International conference on high performance computing in Asia-Pacific Region, pp 111–119

  • Cully A, Clune J, Tarapore D, Mouret JB (2015) Robots that can adapt like animals. Nature 521(7553):503–507

    Article  Google Scholar 

  • Cuzzolin F, Morelli A, Cirstea B, Sahakian BJ (2020) Knowing me, knowing you: theory of mind in ai. psychological. Psychol Med 50(7):1057–1061

    Article  Google Scholar 

  • Demir KA, Doven G, Sezen B (2019) Industry 5.0 and humanrobot co-working. Proc Comput Sci 158:688–695

    Article  Google Scholar 

  • Dereli S, Koker R (2020) A meta-heuristic proposal for inverse kinematics solution of 7-DOF serial robotic manipulator: quantum behaved particle swarm algorithm. Artif Intell Rev 53(2):949–964

    Article  Google Scholar 

  • Dolan RJ (2002) Emotion, cognition, and behavior. Science 298(5596):1191–1194

    Article  Google Scholar 

  • Dong D, Chen C, Zhang C, Chen Z (2006) Quantum robot: structure, algorithms and applications. Robotica 24(4):513–521

    Article  Google Scholar 

  • Dong D, Chen C, Chu J, Tarn TJ (2010) Robust quantum-inspired reinforcement learning for robot navigation. IEEE/ASME Trans Mechatron 17(1):86–97

    Article  Google Scholar 

  • Dong D, Mabrok MA, Petersen IR, Qi B, Chen C, Rabitz H (2015) Sampling-based learning control for quantum systems with uncertainties. Automatica 23(6):2155–2166

    Google Scholar 

  • Dong D, Xing X, Ma H, Chen C, Liu Z, Rabitz H (2019) Learning-based quantum robust control: algorithm, applications, and experiments. IEEE Trans Cybern 50(8):3581–3593

    Article  Google Scholar 

  • Fang B, Zhu J, Zhang H, Wang H, Wang Z (2017) Multi self-interested robot pursuit based on quantum game theory. In: 2017 Chinese automation Congress, pp 7368–7373

  • Fazilat M, Zioui N, St-Arnaud J (2022) A novel quantum model of forward kinematics based on quaternion/Pauli gate equivalence: application to a six-jointed industrial robotic arm. Results Eng 14:100402

    Article  Google Scholar 

  • Fine A (2004) The Einstein-Podolsky-Rosen argument in quantum theory. Stanford Encyclopedia of Philosophy

  • Fingerhuth M, Babej T, Wittek P (2018) Open source software in quantum computing. Plos One 13:e0208561

    Article  Google Scholar 

  • Gao L, Liu R, Wang F, Wu W, Bai B, Yang S, Yao L (2020) An advanced quantum optimization algorithm for robot path planning. J Circ Syst Comput 29(08):2050122

    Article  Google Scholar 

  • Garcia E, Jimenez MA, Santos PGD, Armada M (2007) The evolution of robotics research. IEEE Robot Autom Mag 14(1):90–103

    Article  Google Scholar 

  • Gautam R, Gedam A, Zade A, Mahawadiwar A (2017) Review on development of industrial robotic arm. International Research Journal of. Eng Technol 4(03):1752–1755

    Google Scholar 

  • Gill SS, Kumar A, Singh H, Singh M, Kaur K, Usman M, Buyya R (2022) Quantum computing: a taxonomy, systematic review and future directions. Softw Pract Exp 52(1):66–114

    Article  Google Scholar 

  • Goncalves CP (2019) Quantum robotics, neural networks and the quantum force interpretation. NeuroQuantology 17(2):33–55

    Google Scholar 

  • Goyal M, Sutherland GR, Lama S, Cimflova P, Kashani N, Mayank A, Psychogios M, Spelle L, Costalat V, Sakai N, Ospel JM (2020) Neurointerventional robotics: challenges and opportunities. Clin Neuroradiol 30(2):203–208

    Article  Google Scholar 

  • Guo Q, Quan Y, Liu P, Chen J (2017) Trajectory planning of robot based on quantum genetic algorithm. In: 2017 International conference on mechatronics and intelligent robotics, pp 1185–1192

  • Guo J, Wang X, Zheng X (2010) Trajectory planning of redundant robot manipulators using QPSO algorithm. In: 2010 8th World Congress on intelligent control and automation, pp 403–407

  • Gutmann JS, Fukuchi M, Fujita M (2008) 3D perception and environment map generation for humanoid robot navigation. Int J Robot Res 27(10):1117–1134

    Article  Google Scholar 

  • Heimann D, Hohenfeld H, Wiebe F, Kirchner F (2022) Quantum deep reinforcement learning for robot navigation tasks. arXiv:2202.12180

  • Ho JK, Hoorn JF (2022) Quantum affective processes for multidimensional decision-making. Sci Rep 12(1):20468

    Article  Google Scholar 

  • Hoorn JF (2018) The robot brain server: design of a human-artificial systems partnership. In: 2018 International Conference on Intelligent Human Systems Integration, pp 531–536

  • Hoorn JF, Ho JK (2019) Robot affect: the amygdala as bloch sphere. arXiv:1911.12128

  • Huang D, Wang M, Wang J, Yan J (2022) A survey of quantum computing hybrid applications with brain-computer interface, cognitive. Robotics 2:164–176

    Google Scholar 

  • Izard CE (1977) Human emotions. Plenum Press, New York

    Book  Google Scholar 

  • Jiao M, Chen X, Liu H, Cheng Y, Zhang H (2018) Research on quantum particle swarm optimization in mobile robot path planning for aged service. In: 2018 Chinese control and decision conference, pp 2034–2039

  • Johnston CH (1905) The present state of the psychology of feeling. Psychol Bull 2(5):161

    Article  Google Scholar 

  • Kagan E, Salmona E, Ben-Gal I (2008) Probabilistic mobile robot with quantum decision-making. In: 2008 IEEE convention of electrical and electronics engineers in Israel, pp 418–422

  • Khoshnoud F, Esat II, de Silva CW, Quadrelli MB (2019) Quantum network of cooperative unmanned autonomous systems. Unmanned Syst 7(02):137–145

    Article  Google Scholar 

  • Khoshnoud F, de Silva CW, Esat II (2017) Quantum entanglement of autonomous vehicles for cyber-physical security. In: 2017 IEEE international conference on systems, man, and cybernetics, pp 2655–2660

  • Khoshnoud F, Ghazinejad M (2021) Automated quantum entanglement and cryptography for networks of robotic systems. In: International design engineering technical conferences and computers and information in engineering conference, p V007T07A031

  • Khoshnoud F, Quadrelli MB, Esat II, Robinson D (2020) Quantum cooperative robotics and autonomy. arXiv:2008.12230

  • Kim YH, Kim JH (2009) Multiobjective quantum-inspired evolutionary algorithm for fuzzy path planning of mobile robot. In: 2009 IEEE Congress on evolutionary computation, pp 1185–1192

  • Kitto K (2008) Why quantum theory?, in: 2008 Quantum interaction: proceedings of the 2nd quantum interaction symposium, pp 1–8

  • Kumar A (2018) Methods and materials for smart manufacturing: additive manufacturing, internet of things, flexible sensors and soft robotics. Manuf Lett 15:122–125

    Article  Google Scholar 

  • Kumar AS, Alavandar S (2016) Control of robot manipulator error using FPDI-CIQGA in neural network. J Comput Theor Nanosci 13(3):1740–1748

    Article  Google Scholar 

  • Langley P, Laird JE, Rogers S (2009) Cognitive architectures: research issues and challenges. Cogn Syst Res 10(2):141–160

    Article  Google Scholar 

  • Leitner J (2009) A survey of multi-robot cooperation in space. Transportation 19(22):21

    Google Scholar 

  • Li M (2015) An adaptive quantum evolutionary algorithm and its application to path planning. In: 2015 IEEE international conference on systems, man, and cybernetics, pp 2067–2071

  • Li R, Wu N (2022) Multi-robot source location of scalar fields by a novel swarm search mechanism with collision/obstacle avoidance. IEEE Trans Intell Transp Syst 23(1):249–264

    Article  Google Scholar 

  • Lin C, Wang H, Yuan J, Fu M (2018) An online path planning method based on hybrid quantum ant colony optimization for AUV. Int J Robot Autom 33(4):435–444

    Google Scholar 

  • Liu Y, Li Q, Wang B, Zhang Y, Song D (2023) A survey of quantum-cognitively inspired sentiment analysis models. ACM Comput Surv 56(1):1–37

    Article  Google Scholar 

  • Liu Z, Li X, Jiang J, Wang S (2016) A novel improved quantum genetic algorithm for robot coalition problem. In: 2016 IEEE international conference on information and automation, pp 2061–2064

  • Liu P, Wang B, Liu W, Zhang L (2021) Multi-task allocation of multi-uav coalition based on improved quantum genetic algorithm. In: 2021 Chinese control conference, pp 1802–1807

  • Li R, Wu H (2021) Quantum-behaved multi-robot plume source localization with formation maintenance and obstacle avoidance. In: 2021 Youth Academic Annual Conference of Chinese Association of automation, pp 610–615

  • Li Z, Xu B, Yang L, Chen J, Li K (2009) Quantum evolutionary algorithm for multi-robot coalition formation. In: 2009 ACM/SIGEVO summit on genetic and evolutionary computation, pp 295–302

  • Lukac M, Perkowski M (2007) Quantum mechanical model of emotional robot behaviors. In: 2007 37th International symposium on multiple-valued logic, pp 19–25

  • Lyons W (1999) The philosophy of cognition and emotion. Handbook of Cognition and Emotion. John Wiley & Sons, Chichester, pp 21–44

    Chapter  Google Scholar 

  • Mahanti S, Das S, Behera BK, Panigrahi PK (2019) Quantum robots can fly; play games: an IBM quantum experience. Quantum Inf Process 18(7):1–10

    Article  MathSciNet  Google Scholar 

  • Manju A, Monasubramaniam A (2015) Rule weight tuned fuzzy controller for robot manipulator using quantum inspired firefly algorithm. Power Electron Renew Energy Syst 326:111–119

    Google Scholar 

  • Mannone M, Seidita V, Chella A (2023) Modeling and designing a robotic swarm: a quantum computing approach. Swarm Evol Comput 79:101297

    Article  Google Scholar 

  • Masood A, Gao F, Liu C, Huynh D, Reynolds M, Wang J (2012) A perspective on whether robot localization can be effectively simulated by quantum mechanics. Int J Multidiscip Sci Eng 3(9):15–18

    Google Scholar 

  • Masood A, Gao F, Liu C, Huynh D, Tang Q, Tao Q (2018) A robot SLAM improved by quantum-behaved particles swarm optimization. Math Probl Eng 2018:1596080

    Google Scholar 

  • Mehiar DAF, Azizul ZH, Loo CK (2020) QRDPSO: a new optimization method for swarm robot searching and obstacle avoidance in dynamic environments. Intell Autom Soft Comput 26(3):447–454

    Article  Google Scholar 

  • Mehrabian A, Russell JA (1974) An approach to environmental psychology. the MIT Press, Cambridge, Massachusetts

  • Mouradian C, Sahoo J, Glitho RH, Morrow MJ, Polakos PA (2017) A coalition formation algorithm for multi-robot task allocation in large-scale natural disasters. In: 2017 13th International wireless communications and mobile computing conference, pp 1909–1914

  • Munoz-Saavedra L, Luna-Perejon F, Civit-Masot J, Miro-Amarante L, Civit A, Dominguez-Morales M (2020) Affective state assistant for helping users with cognition disabilities using neural networks. Electronics 9(11):1843

  • Narens L (2016) On replacing “quantum thinking” with counterfactual reasoning. Contextuality from quantum physics to psychology. World Scientific, London, pp 309–324

  • Nayik GA, Muzaffar K, Gull A (2015) Robotics and food technology: a mini review. J Nutr Food Sci 5(4):1–11

    Google Scholar 

  • Nielsen MA, Chuang I (2000) Quantum computation and quantum information. Cambridge university, Cambridge

    Google Scholar 

  • Niu MY, Boixo S, Smelyanskiy VN, Neven H (2019) Universal quantum control through deep reinforcement learning. Npj Quantum Inf 5(1):1–8

    Article  Google Scholar 

  • Ochsner KN, Phelps E (2007) Emerging perspectives on emotion-cognition interactions. Trends Cogn Sci 11(8):317–318

    Article  Google Scholar 

  • Pessoa L (2008) On the relationship between cognition and emotion, Nature Reviews. Neurosciences 9:148–158

    Google Scholar 

  • Petschnigg C, Brandstotter M, Pichler H, Hofbaur M, Dieber B (2019) Quantum computation in robotic science and applications. In: 2019 IEEE international conference on robotics and automation, pp 803–810

  • Plutchik R (1980) A general psychoevolutionary theory of emotion. In: Theories of emotion, pp 3–33

  • Qian Q, Wu J, Wang Z (2019) Optimal path planning for two-wheeled self-balancing vehicle pendulum robot based on quantum-behaved particle swarm optimization algorithm. Pers Ubiquit Comput 23(3):393–403

    Article  Google Scholar 

  • Raghuvanshi A, Fei Y, Woyke M, Perkowski M (2007) Quantum robots for teenagers. In: 2007 37th International symposium on multiple-valued logic, pp 13–16

  • Raghuvanshi A, Perkowski M (2010) Fuzzy quantum circuits to model emotional behaviors of humanoid robots. In: 2010 IEEE Congress on Evolutionary computation, pp 1–8

  • Russell JA (1980) A circumplex model of affect. J Personal Soc Psychol 39(6):1161–1178

    Article  Google Scholar 

  • Saeedvand S, Jafari M, Aghdasi H, Baltes J (2019) A comprehensive survey on humanoid robot development. Knowl Eng Rev 34:e20

    Article  Google Scholar 

  • Sandhie ZT, Patel JA, Ahmed FU, Chowdhury MH (2021) Investigation of multiple-valued logic technologies for beyond-binary era. ACM Comput Surv 54(1):1–30

    Article  Google Scholar 

  • Sarkar M, Pradhan J, Singh A, Nenavath H (2024) A novel hybrid quantum architecture for path planning in quantum-enabled autonomous mobile robots. IEEE Trans Consum Electron. https://doi.org/10.1109/TCE.2024.3423416

    Article  Google Scholar 

  • Schwartz JM, Stapp HP, Beauregard M (2005) Quantum physics in neuroscience and psychology: a neurophysical model of mind-brain interaction. Philos Trans R Soc B Biol Sci 360(1458):1309–1327

    Article  Google Scholar 

  • Song Q, Wang W, Fu W, Sun Y, Wang D, Gao Z (2022) Research on quantum cognition in autonomous driving. Sci Rep 12:300

    Article  Google Scholar 

  • Stefanucci JK, Proffitt DR (2009) The roles of altitude and fear in the perception of height. J Exp Psychol Hum Percept Perform 35(5):424

    Article  Google Scholar 

  • Subashini S, Kavitha V (2011) A survey on security issues in service delivery models of cloud computing. J Netw Comput Appl 34(1):1–11

    Article  Google Scholar 

  • Sun Y, Ding M (2010) Quantum genetic algorithm for mobile robot path planning. In: 2010 IEEE International conference on genetic and evolutionary computing, pp 206–209

  • Tchorzewski J, Rucinski D, Domanski P (2018) Artificial neural network inspired by quantum computing solutions using the movement model of the PR-02 robot. In: 2018 ITM web of conferences, p 01007

  • Toffano Z, Dubois F (2019) Quantum eigenlogic observables applied to the study of fuzzy behaviour of Braitenberg vehicle quantum robots. Kybernetes 48:2307–2324

    Article  Google Scholar 

  • Varma R, Melville C, Pinello C, Sahai T (2021) Post quantum secure command and control of mobile agents inserting quantum-resistant encryption schemes in the secure robot operating system. Int J Semant Comput 15(03):359–379

    Article  Google Scholar 

  • Venegas-Andraca SE, Bose S (2003) Quantum computation and image processing: new trends in artificial intelligence. In: 2003 The international conference on artificial intelligence, pp 1563–1564

  • Vig L, Adams JA (2006) Multi-robot coalition formation. IEEE Trans Robot 22(4):637–649

    Article  Google Scholar 

  • Watson D, Tellegen A (1985) Toward a consensual structure of mood. Psychol Bull 98(2):219

    Article  Google Scholar 

  • Widdows D, Rani J, Pothos E (2023) Quantum circuit components for cognitive decision-making. Entropy 25(4):548

    Article  Google Scholar 

  • Williams Q, Bogner S, Kelley M, Castillo C, Lukac M, Kim DH, Allen JS, Sunardi MI, Hossain S, Perkowski M (2007) An emotional mimicking humanoid biped robot and its quantum control based on the constraint satisfaction model. In: 2007 16th International workshop on Post-Binary ULSI systems, pp 13–16

  • Witvliet CV, Vrana SR (2007) Play it again Sam: repeated exposure to emotionally evocative music polarises liking and smiling responses, and influences other affective reports, facial EMG, and heart rate. Cogn Emot 21(1):3–25

    Article  Google Scholar 

  • Wu C, Huang Y, Hwang J (2016) Review of affective computing in education/learning: trends and challenges. Br J Educ Technol 47(6):1304–1323

    Article  Google Scholar 

  • Yamazaki Y, Hatakeyama Y, Dong F, Nomoto K, Hirota K (2008) Fuzzy inference based mentality expression for Eye robot in affinity pleasure-arousal space. J Adv Comput Intell Intell Inf 12(3):129–146

    Google Scholar 

  • Yan F, Venegas-Andraca SE (2020) Quantum image processing. Springer

    Book  Google Scholar 

  • Yan F, Venegas-Andraca SE (2024) Lessons from twenty years of quantum image processing. ACM Trans Quantum Comput. https://doi.org/10.1145/366357

    Article  Google Scholar 

  • Yan F, Iliyasu AM, Liu Z, Salama AS, Dong F, Hirota K (2015) Bloch sphere-based representation for quantum emotion space. J Adv Comput Intell Intell Inf 19(1):134–142

    Article  Google Scholar 

  • Yan F, Iliyasu AM, Khan AR, Yang H (2016) Measurements-based moving target detection in quantum video. Int J Theor Phys 55(4):2162–2173

    Article  Google Scholar 

  • Yan F, Iliyasu AM, Guo Y, Yang H (2018) Flexible representation and manipulation of audio signals on quantum computers. Theoretical Comput Sci 752:71–85

    Article  MathSciNet  Google Scholar 

  • Yan F, Iliyasu AM, Jiao S, Yang H (2019) Quantum structure for modelling emotion space of robots. Appl Sci 9(16):3351

    Article  Google Scholar 

  • Yan F, Li N, Hirota K (2021) QHSL: a quantum hue, saturation, and lightness color model. Inf Sci 577:196–213

    Article  MathSciNet  Google Scholar 

  • Yan F, Iliyasu AM, Hirota K (2021) Emotion space modelling for social robots. Eng Appl Artif Intell 100:104178

    Article  Google Scholar 

  • Yan F, Iliyasu AM, Hirota K (2021) Conceptual framework for quantum affective computing and its use in fusion of multi-robot emotions. Electronics 10:100

    Article  Google Scholar 

  • Yan F, Huang H, Pedrycz W, Hirota K (2024) Review of medical image processing using quantum-enabled algorithms. Artif Intell Rev 57(11):300

    Article  Google Scholar 

  • Yang X (2022) Fuzzy control path planning of soccer robot relying on quantum genetic algorithm. Mob Inf Syst 2022:3498258

    Google Scholar 

  • Yao J, Huang Y, Zhang Z, Sun C, Zhang X (2017) Minimum-time trajectory planning for an inchworm-like climbing robot based on quantum-behaved particle swarm optimization. Proc Inst Mech Eng Part C J Mech Eng Sci 231(18):3443–3454

    Article  Google Scholar 

  • Yin B, Zhao Z, Xiao H, Liu M, Hu W (2020) Kinematic synthesis of a reconfigurable robot manipulator with lattice morphing mechanisms based on enhanced QPSO. In: IOP conference series: materials science and engineering, p 012032

  • Yu CH, Gao F, Liu C, Huynh D, Reynolds M, Wang J (2019) Quantum algorithm for visual tracking. Phys Rev A 99(2):022301

  • Yu R, Huang W (2009) Design of LMI-based fuzzy controller for robot arm using quantum evolutionary algorithms. In: 2009 International conference on innovative computing, information and control, pp 978–981

  • Zhang Y, Liu S, Fu S, Wu D (2009) A quantum-inspired ant colony optimization for robot coalition formation. In: 2009 Chinese control and decision conference, pp 626–631

  • Zioui N, Mahmoudi Y, Mahmoudi A, Tadjine M, Bentouba S (2021) A new quantum-computing-based algorithm for robotic arms and rigid bodies’ orientation. J Appl Comput Mech 7(3):1836–1846

    Google Scholar 

  • Zitouni F, Maamri R, Harous S (2019) FA-QABC-MRTA: a solution for solving the multi-robot task allocation problem. Intell Serv Robot 12(4):407–418

    Article  Google Scholar 

Download references

Funding

This study was sponsored by the Prince Sattam Bin Abdulaziz University, Saudi Arabia via funding for the Project Number 2023/RV/0005.

Author information

Authors and Affiliations

Authors

Contributions

F.Y.: investigation, conceptualization, methodology, writing—original draft, writing—review and editing. A.M.I.: methodology, validation, formal analysis, writing—review and editing, funding acquisition. N.L.: data curation, visualization, validation, writing—original draft. A.S.S.: formal analysis, writing—review and editing. K.H.: supervision, writing—review and editing.

Corresponding author

Correspondence to Fei Yan.

Ethics declarations

Ethics approval

Not applicable

Consent to participate

All authors read and agreed to participate in the final manuscript.

Consent for publication

All authors agreed to publish this paper if accepted.

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yan, F., Iliyasu, A.M., Li, N. et al. Quantum robotics: a review of emerging trends. Quantum Mach. Intell. 6, 86 (2024). https://doi.org/10.1007/s42484-024-00225-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s42484-024-00225-5

Keywords

Navigation