由於大量與分散的特性，群體機器人是一個具有強大能力的群體系統，讓小型機器人可以透過互相協調合作來完成複雜且超出個體能力的任務。然而，現實世界中任務的複雜程度讓同質的群體機器人並沒有足夠的能力完成，因此，將群體機器人從同質延伸為異構，並且將各種機器人能夠提供的服務進行組合，才能夠實踐群體機器人的強大能力，進而完成現實世界中的複雜任務。
異構群體機器人的特性使它們被認為具有潛力應用在許多的領域中，其中一種是用於代替人類來執行危險性較高的任務，例如未知環境的探索或是戰爭後的地雷排除。這種類型的任務環境通常沒有足夠的網路基礎建設，機器人只能使用對等網路進行局部通訊。因此，受限的連線距離與通訊的安全性，成了群體機器人從理論邁向現實應用的阻礙。區塊鏈是一種起源於比特幣的新興技術，透過結合加密演算法與對等網路，一組特定的代理可以在無須控制權限的情況下進行通訊並保存交易記錄，這樣的特性讓群體機器人在連線距離與通訊管道的問題有了解決方法。使得群體機器人可以在有限的連線距離之下，進行安全且有效的服務組合。
本研究透過讓異構群體機器人在有限的連線距離下透過區塊鏈來完成各種任務，並且利用物聯網服務組合常見的服務品質因子作為評估指標對實驗結果進行評估。根據實驗的結果證明，異構群體機器人透過區塊鏈進行服務組合，除了可以解決對等網路連線距離有限的問題，更在服務品質因子上有著優於傳統對等網路的表現。

Due to the large number and decentralized characteristics, the swarm robotics is a powerful system that allows small robots to coordinate and cooperate with each other to complete complex tasks that exceed individual capabilities. However, the complexity of the task in the real world makes homogeneous swarm robotics unable to complete. Therefore, by extending the swarm robotics from homogeneous to heterogeneous, and composing the services that various robots can provide with each other, can the powerful capabilities of swarm robotics be used to complete complex tasks in the real world.
The characteristics of heterogeneous swarm robotics make them considered to have the potential to be used in many fields, one of which is to replace humans to perform dangerous tasks, such as exploring unknown environments or removing landmines after war. This type of task environment usually does not have enough network infrastructure, and robots can only use peer-to-peer networks for local communication. Therefore, the limited connection distance and safe communication channels have become obstacles that prevent swarm robotics from moving from theory to practical applications. Blockchain is an emerging technology that originated from Bitcoin. By combining encryption algorithms and peer-to-peer networks, a group of specific agents can communicate and save transaction records without controlling authority. This allows the swarm robotics to have a solution to the problem of the connection distance and the communication channel. Allow swarm robotics to perform safe and effective service composition within a limited connection distance.
This research designed an experiment to allow heterogeneous swarm robotics to complete various tasks through the blockchain under a limited connection distance, and use the the Quality of Service (QoS) in IoT environment to evaluate the experiment results. According to the experimental results, the heterogeneous swarm robotics composed services through the blockchain not only solves the problem of the limited connection distance of peer-to-peer networks, but also has better performance than traditional peer-to-peer networks.

論文審定書 i
摘要 ii
Abstract iii
圖目錄 vii
表目錄 viii
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 3
1.3 研究問題與目的 6
第二章 文獻探討 7
2.1 區塊鏈與智能合約 7
2.2 服務組合 10
2.3 群體機器人技術 11
第三章 研究方法 14
3.1 分散式集體決策 14
3.2 系統框架 16
3.2.1 服務登錄 19
3.2.2 更新狀態 22
3.2.3 服務詢問 24
3.2.4 服務選擇與尋求協助 25
3.2.5 追蹤任務 28
3.3 問題定義 32
第四章 實驗 35
4.1 實驗介紹 35
4.1.1 對等網路 38
4.1.2 區塊鏈 38
4.2 實驗環境 39
4.3 評估指標 39
第五章 實驗結果 41
5.1 實驗設置 41
5.2 任務執行時間 44
5.2.1 固定機器人數量 44
5.2.2 固定任務數量 48
5.3 機器人能量消耗 51
5.3.1 固定機器人數量 51
5.3.2 固定任務數量 55
5.4 實驗結論 59
第六章 結論 60
6.1 結論 60
6.2 未來展望 61
參考文獻 62

[1] E. Şahin, "Swarm robotics: From sources of inspiration to domains of application," in International workshop on swarm robotics, 2004: Springer, pp. 10-20.
[2] J. Kennedy, "Swarm intelligence," in Handbook of Nature-Inspired and Innovative Computing: Springer, 2006, pp. 187-219.
[3] M. Dorigo, M. Birattari, and M. Brambilla, "Swarm robotics," Scholarpedia, vol. 9, no. 1, p. 1463, 2014.
[4] M. Brambilla, E. Ferrante, M. Birattari, and M. Dorigo, "Swarm robotics: a review from the swarm engineering perspective," Swarm Intelligence, vol. 7, no. 1, pp. 1-41, 2013.
[5] J. P. Queralta and T. Westerlund, "Blockchain-powered collaboration in heterogeneous swarms of robots," Frontiers in Robotics and AI, 2020.
[6] E. C. Ferrer, "The blockchain: a new framework for robotic swarm systems," in Proceedings of the Future Technologies Conference, 2018: Springer, pp. 1037-1058.
[7] B. K. Mohanta, S. S. Panda, and D. Jena, "An overview of smart contract and use cases in blockchain technology," in 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2018: IEEE, pp. 1-4.
[8] L. Lamport, R. Shostak, and M. Pease, "The Byzantine generals problem," in Concurrency: the Works of Leslie Lamport, 2019, pp. 203-226.
[9] M. Dorigo et al., "Swarmanoid: a novel concept for the study of heterogeneous robotic swarms," IEEE Robotics & Automation Magazine, vol. 20, no. 4, pp. 60-71, 2013.
[10] M. G. S. De Campos, C. P. Chanel, C. Chauffaut, and J. Lacan, "Towards a blockchain-based multi-UAV surveillance system," Frontiers in Robotics and AI, vol. 8, 2021.
[11] J. Grey, I. Godage, and O. Seneviratne, "Swarm contracts: Smart contracts in robotic swarms with varying agent behavior," in 2020 IEEE International Conference on Blockchain (Blockchain), 2020: IEEE, pp. 265-272.
[12] J. P. Queralta, J. Raitoharju, T. N. Gia, N. Passalis, and T. Westerlund, "AutoSOS: Towards multi-UAV systems supporting maritime search and rescue with lightweight AI and edge computing," arXiv preprint arXiv:2005.03409, 2020.
[13] S. Nakamoto, "Bitcoin: A peer-to-peer electronic cash system," Manubot, 2019.
[14] R. Böhme, N. Christin, B. Edelman, and T. Moore, "Bitcoin: Economics, technology, and governance," Journal of Economic Perspectives, vol. 29, no. 2, pp. 213-38, 2015.
[15] K. P. Sycara, "Multiagent systems," AI Magazine, vol. 19, no. 2, pp. 79-79, 1998.
[16] V. Buterin, "A next-generation smart contract and decentralized application platform," White Paper, vol. 3, no. 37, 2014.
[17] G. Wood, "Ethereum: A secure decentralised generalised transaction ledger," Ethereum Project Yellow Paper, vol. 151, no. 2014, pp. 1-32, 2014.
[18] J. Ellul and G. J. Pace, "Alkylvm: A virtual machine for smart contract blockchain connected internet of things," in 2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS), 2018: IEEE, pp. 1-4.
[19] J. Li, A. Grintsvayg, J. Kauffman, and C. Fleming, "LBRY: A blockchain-based decentralized digital content marketplace," in 2020 IEEE International Conference on Decentralized Applications and Infrastructures (DAPPS), 2020: IEEE, pp. 42-51.
[20] T. T. Nguyen, A. Hatua, and A. H. Sung, "Blockchain approach to solve collective decision making problems for swarm robotics," in International Congress on Blockchain and Applications, 2019: Springer, pp. 118-125.
[21] M. N. Huhns and M. P. Singh, "Service-oriented computing: Key concepts and principles," IEEE Internet computing, vol. 9, no. 1, pp. 75-81, 2005.
[22] P. Asghari, A. M. Rahmani, and H. H. S. Javadi, "Service composition approaches in IoT: A systematic review," Journal of Network and Computer Applications, vol. 120, pp. 61-77, 2018.
[23] Z. Jin, "Chapter 13 - Other nonfunctionality patterns," in Environment Modeling-Based Requirements Engineering for Software Intensive Systems, Z. Jin Ed. Oxford: Morgan Kaufmann, 2018, pp. 241-261.
[24] G. J. Holzmann and D. Peled, "An improvement in formal verification," in Formal Description Techniques VII: Springer, 1995, pp. 197-211.
[25] E. M. Clarke, "Model checking," in International Conference on Foundations of Software Technology and Theoretical Computer Science, 1997: Springer, pp. 54-56.
[26] M. Alodib, "QoS-Aware approach to monitor violations of SLAs in the IoT," Journal of Innovation in Digital Ecosystems, vol. 3, no. 2, pp. 197-207, 2016.
[27] J. Guerrero and G. Oliver, "Multi-robot coalition formation in real-time scenarios," Robotics and Autonomous Systems, vol. 60, no. 10, pp. 1295-1307, 2012.
[28] J. Chen and D. Sun, "Resource constrained multirobot task allocation based on leader–follower coalition methodology," The International Journal of Robotics Research, vol. 30, no. 12, pp. 1423-1434, 2011.
[29] M.-H. Kim, S.-P. Kim, and S. Lee, "Social-welfare based task allocation for multi-robot systems with resource constraints," Computers & Industrial Engineering, vol. 63, no. 4, pp. 994-1002, 2012.
[30] G. Beni and J. Wang, "Swarm intelligence in cellular robotic systems," in Robots and Biological Systems: Towards a New Bionics?: Springer, 1993, pp. 703-712.
[31] E. Bonabeau, M. Dorigo, D. d. R. D. F. Marco, G. Theraulaz, and G. Théraulaz, Swarm intelligence: from natural to artificial systems (no. 1). Oxford university press, 1999.
[32] V. Strobel, E. C. Ferrer, and M. Dorigo, "Managing byzantine robots via blockchain technology in a swarm robotics collective decision making scenario," presented at the Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, Stockholm, Sweden, 2018.
[33] V. Lopes, L. A. Alexandre, and N. Pereira, "Controlling robots using artificial intelligence and a consortium blockchain," arXiv preprint arXiv:1903.00660, 2019.
[34] G. P. Das, T. M. McGinnity, S. A. Coleman, and L. Behera, "A fast distributed auction and consensus process using parallel task allocation and execution," in 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011: IEEE, pp. 4716-4721.
[35] I. Navarro and F. Matía, "A framework for the collective movement of mobile robots based on distributed decisions," Robotics and Autonomous Systems, vol. 59, no. 10, pp. 685-697, 2011.
[36] R. Aragues, C. Sagues, and Y. Mezouar, "Feature-based map merging with dynamic consensus on information increments," Autonomous Robots, vol. 38, no. 3, pp. 243-259, 2015.
[37] T. Kundu and I. Saha, "Mobile recharger path planning and recharge scheduling in a multi-robot environment," arXiv preprint arXiv:2102.12296, 2021.
[38] P. Dasgupta, J. Baca, K. Guruprasad, A. Muñoz-Meléndez, and J. Jumadinova, "The comrade system for multirobot autonomous landmine detection in postconflict regions," Journal of Robotics, vol. 2015, 2015.
[39] S. Alers, K. Tuyls, B. Ranjbar-Sahraei, D. Claes, and G. Weiss, "Insect-inspired robot coordination: foraging and coverage," in ALIFE 14: The Fourteenth International Conference on the Synthesis and Simulation of Living Systems, 2014: MIT Press, pp. 761-768.
[40] A. Campo and M. Dorigo, "Efficient multi-foraging in swarm robotics," in European Conference on Artificial Life, 2007: Springer, pp. 696-705.
[41] F. Mondada et al., "The e-puck, a robot designed for education in engineering," in Proceedings of the 9th conference on autonomous robot systems and competitions, 2009, vol. 1, no. CONF: IPCB: Instituto Politécnico de Castelo Branco, pp. 59-65.
[42] C. Pinciroli et al., "ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems," Swarm Intelligence, vol. 6, no. 4, pp. 271-295, 2012.