A new fuzzy speed planning method for safe navigation

Sezer, Volkan; Ercan, Ziya; Heceoglu, H.; Boğosyan, Seta; Gökaşan, Metin

doi:10.1109/icves.2012.6294308

Cited by 7 publications

(6 citation statements)

References 13 publications

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“…This value is selected small similar to the output of a fuzzy-logic-based longitudinal velocity planner, mentioned in ref. [35]. The mentioned heading angle controller is introduced in Eq.…”

Section: Simulation Resultsmentioning

confidence: 99%

A new gap-based obstacle avoidance approach: follow the obstacle circle method

Houshyari

Sezer

2021

Robotica

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One of the most challenging tasks for autonomous robots is avoiding unexpected obstacles during their path following operation. Follow the gap method (FGM) is one of the most popular obstacle avoidance algorithms that recursively guides the robot to the goal state by considering the angle to the goal point and the distance to the closest obstacles. It selects the largest gap around the robot, where the gap angle is calculated by the vector to the midpoint of the largest gap. In this paper, a novel obstacle avoidance procedure is developed and applied to a real fully autonomous wheelchair. This proposed algorithm improves the FGM’s travel safety and brings a new solution to the obstacle avoidance task. In the proposed algorithm, the largest gap is selected based on gap width. Moreover, the avoidance angle (similar to the gap center angle of FGM) is calculated considering the locus of the equidistant points from obstacles that create obstacle circles. Monte Carlo simulations are used to test the proposed algorithm, and according to the results, the new procedure guides the robot to safer trajectories compared with classical FGM. The real experimental test results are in parallel to the simulations and show the real-time performance of the proposed approach.

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Section: Simulation Resultsmentioning

confidence: 99%

A new gap-based obstacle avoidance approach: follow the obstacle circle method

Houshyari

Sezer

2021

Robotica

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“…In the fuzzy-based speed planning method, which was developed for autonomous systems [22,23], the speed of the system is adjusted by calculating the risk coming from the obstacles in the environment. The risk factor is calculated for each obstacle with the help of fuzzy logic, by using obstacle positions within the vehicle's field of view.…”

Section: Fuzzy Speed Planning For Autonomous Systemsmentioning

confidence: 99%

“…The speed planning method, which determines the linear speed of a vehicle by using fuzzy logic according to the risk factor of the environment, was designed for autonomous vehicles [22,23]. Speed planning for semiautonomous systems must combine both the speed reference obtained by the risk factor and the speed reference that is given by the user.…”

Section: Fuzzy Speed Planning For Semiautonomous Systemsmentioning

confidence: 99%

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Design and implementation of a new speed planner for semiautonomous systems

Demir¹,

Sezer²

2018

Turk J Elec Eng & Comp Sci

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In this paper, a new speed planning method is developed for semiautonomous systems by improving our previous fuzzy logic-based approach. In this proposed method, an extended risk factor is calculated on top of the classical risk factor, using environmental factors and the user's speed reference. We obtain safer speed values in critical scenarios with this new extended risk factor definition. Another improvement comes from the design of the semiautonomous architecture. Instead of the fully autonomous solution of the previous work, we calculate the final speed reference by combining the risk factor-based speed value and user's speed reference, which provides a semiautonomous solution. The developed fuzzy logic-based semiautonomous speed planner was tested in simulations and real environments on a differential drive wheelchair platform controlled via head movements. The results of the tests show that the proposed fuzzy-based semiautonomous speed planner using an extended risk factor provides safer transportation than its previous variant.

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“…BKV, daha önce yine tam otonom araçlar için geliştirilmiş, engellerin oluşturduğu risklere göre hız planlaması yapan bir yaklaşımdır [12,14]…”

Section: Hız Planlayıcı Desteği (Speed Planning Support)unclassified

Kafa Hareketleri̇yle Kontrol Edi̇lebi̇len Yari-Otonom Elektri̇kli̇ Tekerlekli̇ Sandalye Geli̇şti̇ri̇lmesi̇

Sezer

2018

Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım Ve Teknoloji

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Bu makalede, kafa hareketleriyle kontrol edilebilen yarı-otonom elektrikli tekerlekli sandalyenin tasarımına ve geliştirilmesine yönelik yapılan çalışmalar anlatılmaktadır. Sistemin istenen düzeyde çalışabilmesi için çeşitli algoritmalar, tanımlanan problem özelinde sisteme adapte edilmiştir. Kullanıcı önceden tanımlanmış özel kafa hareketleriyle sistemi açıp kapayabilmekte; yarı-otonom destekli ve desteksiz sürüş modlarına sokabilmektedir. Çalışmanın ana kapsamını oluşturan destekli sürüş modunda, hatalı kullanıcı girişlerinin tehlikeli sonuçlara dönüşmemesi için yarı-otonom sistem sürüşe destek olmakta ve gerektiği durumlarda değişen oranlarda devreye girerek sürüşü iyileştirmektedir. Yapılan geliştirmeler gerçek bir tekerlekli sandalye platformu üzerinde başarıyla uygulanmış ve sonuçlar incelenmiştir Design of a Semi-Autonomous Electric Wheelchair Controlled by Head Movements

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A new fuzzy speed planning method for safe navigation

Cited by 7 publications

References 13 publications

A new gap-based obstacle avoidance approach: follow the obstacle circle method

A new gap-based obstacle avoidance approach: follow the obstacle circle method

Design and implementation of a new speed planner for semiautonomous systems

Kafa Hareketleri̇yle Kontrol Edi̇lebi̇len Yari-Otonom Elektri̇kli̇ Tekerlekli̇ Sandalye Geli̇şti̇ri̇lmesi̇

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