Noktasal Kontağa Sahip Zıplayan Robotta Duruş Anında Dengenin Sağlanması

Year 2024, , 593 - 607, 30.09.2024

Halit Hülako

https://doi.org/10.35234/fumbd.1415814

Abstract

Bu çalışmada, yer ile noktasal bir temas yüzeyine sahip olan zıplayan düzlemsel dinamik bir robotun zıplama sonrasında devrilmeden dengesini koruması incelenmiştir. Robotun dengesini sağlamak için Reaksiyon Tekerleği kullanılmıştır. Zıplama sonrasında yere iniş anı simüle edilmiş ve robotun yere temas ettiği anda dengesini koruyarak istikrarlı bir duruş sergilemesi için Genetik algoritma kullanarak Pekiştirmeli Öğrenme (PÖ) yapısına benzer bir Yapay Zeka Ajanı oluşturulmuştur. Bu yöntemle zıplayan robot, gerçek zamanlı olarak dengelenme misyonu için eğitilmiş ve ardından robotun dengeleme işlemini başarıyla öğrendiği gözlemlenmiştir. Zıplayan robotun dinamik modellemesi Matlab Simscape MultiBody (MSM) kullanılarak gerçekleştirilmiştir. Nümerik Simülasyona ait grafiksel sonuçlar, dinamik robot modelinin, zıplamadan sonra devrilmeden dengesini 5 saniye boyunca başarıyla sürdürdüğünü ve istenen düzeltmeleri yapabilme yeteneğini Yapay Zeka' nın katkısıyla sergilediğini göstermektedir.

Keywords

Zıplayan robot, E. pekiştirmeli öğrenme, reaksiyon tekeri.

Maintaining Stability During Rest for Jumping Robot with Point Contact

Abstract

This study investigates a planar modelled dynamic jumping robot with a point ground contact surface. The aim is to maintain the robot's balance after jumping without tipping over. To achieve this, a Reaction Wheel is employed for stabilization. The landing moment after a jump is simulated, and an Artificial Intelligence algorithm similiar to Reinforcement Learning (RL), which uses Genetic algorithm, is used to maintain a stable posture by maintaining balance at the moment the robot touches the ground. With this method, the jumping robot was trained for the stabilisation mission in real-time and then it was observed that the robot successfully learnt the stabilisation process. The jumping robot's dynamic modelling was carried out using Matlab Simscape MultiBody (MSM). The graphical results of the numerical simulation show that the dynamic robot model successfully maintains its balance for 5 seconds without tipping over after jumping and exhibits the ability to make the desired corrections with the contribution of Artificial Intelligence.

Keywords

Jumping robot, E. reinforcement learning, reaction wheel.

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