{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T21:56:23Z","timestamp":1747173383814,"version":"3.40.5"},"reference-count":17,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2020,7,14]],"date-time":"2020-07-14T00:00:00Z","timestamp":1594684800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotica"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:title>SUMMARY<\/jats:title><jats:p>Today, robots can be found helping humans with their daily tasks. Some tasks require the robot to visit a set of locations in the environment efficiently, like in the Traveling Salesman Problem. As indoor environments are maze-like areas, feasible paths connecting locations must be computed beforehand, so they can be combined during the scheduling, which can be impracticable for real-time applications. This work presents an on-line Route Scheduling supported by a Fast Path Planning Method able to adjust pre-built paths. Experiments were carried out with virtual and real robots to evaluate time and quality of tours.<\/jats:p>","DOI":"10.1017\/s0263574720000594","type":"journal-article","created":{"date-parts":[[2020,7,14]],"date-time":"2020-07-14T10:37:45Z","timestamp":1594723065000},"page":"3-15","source":"Crossref","is-referenced-by-count":1,"title":["Speeding Up On-Line Route Scheduling for an Autonomous Robot Through Pre-Built Paths"],"prefix":"10.1017","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5429-9595","authenticated-orcid":false,"given":"Raul","family":"Alves","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Josu\u00e9 Silva","family":"de Morais","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keiji","family":"Yamanaka","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2020,7,14]]},"reference":[{"volume-title":"Genetic Algorithms in Search, Optimization and Machine Learning","year":"1989","author":"Goldberg","key":"S0263574720000594_ref17"},{"key":"S0263574720000594_ref16","unstructured":"16. Le, C. , Pham, H. X and La, H. M. , \u201cA Multi-Robotic System for Environmental Cleaning,\u201d CoRR available at: http:\/\/arxiv.org\/abs\/1811.00690 (2018)."},{"key":"S0263574720000594_ref15","unstructured":"15. Ghadiry, W. , Habibi, J. , Aghdam, A. G. and Zhang, Y. , \u201cTime-Efficient Trajectory Optimization in Patrolling Problems with Non-Prespecified Depots and Robots,\u201d Proceedings of the 24th Mediterranean Conference on Control and Automation (IEEE-MED), Athens, Greece (2016) pp. 1047\u20131052."},{"key":"S0263574720000594_ref14","unstructured":"14. Cheng, J. , Miao, Z. , Li, B. and Xu, W. , \u201cAn Improved ACO Algorithm for Mobile Robot Path Planning,\u201d Proceedings of the International Conference on Information and Automation (IEEE-ICIA), Ningbo, China (2016) pp. 963\u2013968."},{"key":"S0263574720000594_ref13","unstructured":"13. Tsilomitrou, O. , Evangeliou, N. and Tzes, A. , \u201cMobile Robot Tour Scheduling Acting as Data Mule in a Wireless Sensor Network,\u201d Proceedings of the 5th International Conference on Control, Decision and Information Technologies (IEEE-CoDIT), Thessaloniki, Greece (2018) pp. 327\u2013332."},{"key":"S0263574720000594_ref11","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574714000393"},{"key":"S0263574720000594_ref12","first-page":"521","article-title":"Solving an agricultural robot routing problem with binary particle swarm optimization and a genetic algorithm","volume":"7","author":"Azimi","year":"2018","journal-title":"Int. J. Mech. Eng. Rob. 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