Automated Training Plan Generation For Athletes

Tomáš ŠkeřÍk, Lukáš Chrpa, Wolfgang Faber, Mauro Vallati

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)


In sports, athletes need detailed and individualised training plans for maintaining and improving their skills in order to achieve their best performance in competitions. This presents a considerable workload for coaches, who besides setting objectives have to formulate extremely detailed training plans. Automated Planning, which has already been successfully deployed in many real-world applications such as space exploration, robotics, and manufacturing processes, embodies a useful mechanism that can be exploited for generating training plans for athletes. In this paper, we propose the use of Automated Planning techniques for generating individual training plans, which consist of exercises the athlete has to perform during training, given the athlete’s current performance, period of time, and target performance that should be achieved. Our experimental analysis, which considers general training of kickboxers, shows that apart of considerable less planning time, training plans automatically generated by the proposed approach are more detailed and individualised than plans prepared manually by an expert coach.
Original languageEnglish
Title of host publication2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC2018)
Number of pages6
ISBN (Electronic)9781538666500
ISBN (Print)9781538666517
Publication statusPublished - 17 Jan 2019
EventIEEE International Conference on Systems, Man, and Cybernetics - Miyazaki, Japan
Duration: 7 Oct 201810 Oct 2018 (Link to Conference Website)


ConferenceIEEE International Conference on Systems, Man, and Cybernetics
Abbreviated titleSMC2018
Internet address


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