Development and Bench-marking of Agoraphilic Navigation Algorithm in Dynamic Environment

Hewawasam, H.S.; Ibrahim, M. Yousef; Kahandawa, Gayan; Choudhury, T. A.

doi:10.1109/isie.2019.8781352

Cited by 7 publications

(10 citation statements)

References 26 publications

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“…The Agoraphilic navigation algorithm has been developed to overcome many challenges in mobile robot navigation. The work presented in this paper is a continuation of authors previous work involved with Agoraphilic algorithm [1]- [3].…”

Section: Introductionmentioning

confidence: 78%

Evaluating the Performances of the Agoraphilic Navigation Algorithm under Dead-Lock Situations

Hewawasam

Ibrahim

Kahandawa

et al. 2020

2020 IEEE 29th International Symposium on Industrial Electronics (ISIE)

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This paper presents a summary of the research which was conducted in developing a new free-space based (Agoraphilic) navigation algorithm. This new methodology is capable of maneuvering robots in static as well as dynamically cluttered unknown environments. The new algorithm uses only one force to drive the robot. This force is always an attractive force created by the freespace. This force is focused towards the goal by a force shaping module. Consequently, the robot is motivated to follow free-space directing towards the goal. As this method only based on the attractive forces, the robot always moves towards the goal as long as there is free-space available. This method has eradicated many drawbacks of the traditional APF method. Several experimental tests were conducted using Turtlebot3 research platform. These tests were focused on testing the behavior of the new algorithm under deadlock (local minima) situations for APF method. The test results proved that the proposed algorithm has successfully eliminated the local minima problem of APF method.

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Section: Introductionmentioning

confidence: 78%

Evaluating the Performances of the Agoraphilic Navigation Algorithm under Dead-Lock Situations

Hewawasam

Ibrahim

Kahandawa

et al. 2020

2020 IEEE 29th International Symposium on Industrial Electronics (ISIE)

Self Cite

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“…2. When generating initial force (F k ), if the distance in FSH corresponding to that sector (d k ) is greater than pre-determined dmax the initial force of the sector is taken as uk [4]. These initial forces are known as FSFs.…”

Section: B Agoraphlic Navigation Algorithm Under Dynamic Environmentmentioning

confidence: 99%

“…The Artificial Potential Field (APF) concept was introduced by Khatib [1]. Although the APF method is relatively simple, there are several well-documented problems associated with APF [2], [3], [4]. Such as, 1) When there is an obstacle close to the goal robot can't reach the goal.…”

Section: Introductionmentioning

confidence: 99%

“…The authors' previous work was involved in eliminating this limitation of Agoraphilic algorithm [4]. This paper presents the new additional improvements done to the Agoraphlic algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…This improvement achieved by predicting future locations of moving objects in dynamically cluttered environments. These improvements have allowed the robot to navigate in dynamic environments more efficiently in terms of path length, speed and decision making compared with the previous methodologies [4].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Agoraphilic Navigation Algorithm in Dynamic Environment with and without Prediction of Moving Objects Location

Hewawasam

Ibrahim

Kahandawa

et al. 2019

IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society

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This paper presents a summary of research conducted in performance improvement of Agoraphilic Navigation Algorithm under Dynamic Environment (ANADE). The ANADE is an optimistic navigation algorithm which is capable of navigating robots in static as well as in unknown dynamic environments. ANADE has been successfully extended the capacity of original Agoraphilic algorithm for static environment. However, it could identify that ANADE takes costly decisions when it is used in complex dynamic environments. The proposed algorithm in this paper has been successfully enhanced the performance of ANADE in terms of safe travel, speed variation, path length and travel time. The proposed algorithm uses a prediction methodology to estimate future growing free space passages which can be used for safe navigation of the robot. With motion prediction of moving objects, new set of future driving forces were developed. These forces has been combined with present driving force for safe and efficient navigation. Furthermore, the performances of proposed algorithm (Agoraphilic algorithm with prediction) was compared and benchedmarked with ANADE (Without predication) under similar environment conditions. Form the investigation results, it was observed that the proposed algorithm extends the effective decision making ability in a complex navigation environment. Moreover, the proposed algorithm navigated the robot in a shorter and quicker path with smooth speed variations.

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Agoraphilic navigation algorithm in dynamic environment with obstacles motion tracking and prediction

et al. 2021

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This paper presents a new algorithm to navigate robots in dynamically cluttered environments. The proposed algorithm uses basic concepts of space attraction (hence the term Agoraphilic) to navigate robots through dynamic obstacles. The new algorithm in this paper is an advanced development of the original Agoraphilic navigation algorithm that was only able to navigate robots in static environments. The Agoraphilic algorithm does not look for obstacles (problems) to avoid but rather for a free space (solutions) to follow. Therefore, it is also described as an optimistic navigation algorithm. This algorithm uses only one attractive force created by the available free space. The free-space concept allows the Agoraphilic algorithm to overcome inherited challenges of general navigation algorithms. However, the original Agoraphilic algorithm has the limitation in navigating robots only in static, not in dynamic environments. The presented algorithm was developed to address this limitation of the original Agoraphilic algorithm. The new algorithm uses a developed object tracking module to identify the time-varying free spaces by tracking moving obstacles. The capacity of the algorithm was further strengthened by the new prediction module. Future space prediction allowed the algorithm to make decisions considering future growing/diminishing free spaces. This paper also includes a bench-marking study of the new algorithm compared with a recently published APF-based algorithm under a similar operating environment. Furthermore, the algorithm was validated based on experimental tests and simulation tests.

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Development and Bench-marking of Agoraphilic Navigation Algorithm in Dynamic Environment

Cited by 7 publications

References 26 publications

Evaluating the Performances of the Agoraphilic Navigation Algorithm under Dead-Lock Situations

Evaluating the Performances of the Agoraphilic Navigation Algorithm under Dead-Lock Situations

Agoraphilic Navigation Algorithm in Dynamic Environment with and without Prediction of Moving Objects Location

Agoraphilic navigation algorithm in dynamic environment with obstacles motion tracking and prediction

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