A novel optimistic local path planner : agoraphilic navigation algorithm in dynamic environment
- Hewawasam, Hasitha, Ibrahim, Yousef, Kahandawa, Gayan
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan
- Date: 2022
- Type: Text , Journal article
- Relation: Machines Vol. 10, no. 11 (2022), p.
- Full Text:
- Reviewed:
- Description: This paper presents a novel local path planning algorithm developed based on the new free space attraction (Agoraphilic) concept. The proposed algorithm is capable of navigating robots in unknown static, as well as dynamically cluttered environments. Unlike the other navigation algorithms, the proposed algorithm takes the optimistic approach of the navigation problem. It does not look for problems to avoid, but rather for solutions to follow. This human-like decision-making behaviour distinguishes the new algorithm from all the other navigation algorithms. Furthermore, the new algorithm utilises newly developed tracking and prediction algorithms, to safely navigate mobile robots. This is further supported by a fuzzy logic controller designed to efficiently account for the inherent high uncertainties in the robot’s operational environment at a reduced computational cost. This paper also includes physical experimental results combined with bench-marking against other recent methods. The reported results verify the algorithm’s successful advantages in navigating robots in both static and dynamic environments. © 2022 by the authors.
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan
- Date: 2022
- Type: Text , Journal article
- Relation: Machines Vol. 10, no. 11 (2022), p.
- Full Text:
- Reviewed:
- Description: This paper presents a novel local path planning algorithm developed based on the new free space attraction (Agoraphilic) concept. The proposed algorithm is capable of navigating robots in unknown static, as well as dynamically cluttered environments. Unlike the other navigation algorithms, the proposed algorithm takes the optimistic approach of the navigation problem. It does not look for problems to avoid, but rather for solutions to follow. This human-like decision-making behaviour distinguishes the new algorithm from all the other navigation algorithms. Furthermore, the new algorithm utilises newly developed tracking and prediction algorithms, to safely navigate mobile robots. This is further supported by a fuzzy logic controller designed to efficiently account for the inherent high uncertainties in the robot’s operational environment at a reduced computational cost. This paper also includes physical experimental results combined with bench-marking against other recent methods. The reported results verify the algorithm’s successful advantages in navigating robots in both static and dynamic environments. © 2022 by the authors.
Agoraphilic navigation algorithm in dynamic environment
- Authors: Hewawasam, Hasitha
- Date: 2021
- Type: Text , Thesis , PhD
- Full Text:
- Description: This thesis presents a novel Agoraphilic (free space attraction [FSA])-based navigation algorithm. This new algorithm is capable of undertaking local path planning for robot navigation in static and dynamic environments with the presence of a moving goal. The proposed algorithm eliminates the common weaknesses of the existing navigation approaches when operating in unknown dynamic environments while using the modified Agoraphilic concept. The Agoraphilic Navigation Algorithm in Dynamic Environment (ANADE) presented in this thesis does not look for obstacles (problems) to avoid; rather, it looks for free space (solutions) to follow. Therefore, this algorithm is also a human-like optimistic navigation algorithm. The proposed algorithm creates a set of Free Space Forces (FSFs) based on the current and future growing free space around the robot. These Free Space Forces are focused towards the current and future locations of a moving goal and finally generate a single attractive force. This attractive force pulls the robot through current free space towards the future growing free space leading to the goal. The new free space concept allows the ANADE to overcome many common problems of navigation algorithms. Several versions of the ANADE have been developed throughout this research to overcome the main limitation of the original Agoraphilic algorithm and address the common weaknesses of the existing navigation approaches. The ANADE I uses an object tracking method to identify the states (locations) of moving objects accurately. The ANADE II uses a dynamic obstacle prediction methodology to identify the robot’s future environments. In the ANADE III, a novel controller based on fuzzy logic was developed and combined with the new FSA concept to provide optimal navigational solutions at a low computational cost. In the ANADE III, the effectiveness of the ANADE II was further improved by incorporating the velocity vectors of the moving objects into decision-making. In the ANADE IV, a self-tuning system was successfully applied to the ANADE III to take advantage of the performances of free space attraction-based navigation algorithms. The proposed final version of the algorithm (ANADE V) comprises nine main modules. These modules are repeatedly used to create the robot’s driving force, which pulls the robot towards the goal (moving or static). An obstacle tracking module is used to identify the time-varying free spaces by tracking the moving objects. Further, a tracking system is also used to track the moving goal. The capacity of the ANADE was strengthened further by obstacle and goal path prediction modules. Future location prediction allowed the algorithm to make decisions by considering future environments around the robot. This is further supported by a self-tuning, machine learning–based controller designed to efficiently account for the inherent high uncertainties in the robot’s operational environment at a reduced computational cost. Experimental and simulation-based tests were conducted under dynamic environments to validate the algorithm. Further, the ANADE was benchmarked against other recently developed navigation algorithms. Those tests were focused on the behaviour of the algorithm under challenging environments with moving and static obstacles and goals. Further, the test results demonstrate that the ANADE is successful in navigating robots under unknown, dynamically cluttered environments.
- Description: Doctor of Philosophy
- Authors: Hewawasam, Hasitha
- Date: 2021
- Type: Text , Thesis , PhD
- Full Text:
- Description: This thesis presents a novel Agoraphilic (free space attraction [FSA])-based navigation algorithm. This new algorithm is capable of undertaking local path planning for robot navigation in static and dynamic environments with the presence of a moving goal. The proposed algorithm eliminates the common weaknesses of the existing navigation approaches when operating in unknown dynamic environments while using the modified Agoraphilic concept. The Agoraphilic Navigation Algorithm in Dynamic Environment (ANADE) presented in this thesis does not look for obstacles (problems) to avoid; rather, it looks for free space (solutions) to follow. Therefore, this algorithm is also a human-like optimistic navigation algorithm. The proposed algorithm creates a set of Free Space Forces (FSFs) based on the current and future growing free space around the robot. These Free Space Forces are focused towards the current and future locations of a moving goal and finally generate a single attractive force. This attractive force pulls the robot through current free space towards the future growing free space leading to the goal. The new free space concept allows the ANADE to overcome many common problems of navigation algorithms. Several versions of the ANADE have been developed throughout this research to overcome the main limitation of the original Agoraphilic algorithm and address the common weaknesses of the existing navigation approaches. The ANADE I uses an object tracking method to identify the states (locations) of moving objects accurately. The ANADE II uses a dynamic obstacle prediction methodology to identify the robot’s future environments. In the ANADE III, a novel controller based on fuzzy logic was developed and combined with the new FSA concept to provide optimal navigational solutions at a low computational cost. In the ANADE III, the effectiveness of the ANADE II was further improved by incorporating the velocity vectors of the moving objects into decision-making. In the ANADE IV, a self-tuning system was successfully applied to the ANADE III to take advantage of the performances of free space attraction-based navigation algorithms. The proposed final version of the algorithm (ANADE V) comprises nine main modules. These modules are repeatedly used to create the robot’s driving force, which pulls the robot towards the goal (moving or static). An obstacle tracking module is used to identify the time-varying free spaces by tracking the moving objects. Further, a tracking system is also used to track the moving goal. The capacity of the ANADE was strengthened further by obstacle and goal path prediction modules. Future location prediction allowed the algorithm to make decisions by considering future environments around the robot. This is further supported by a self-tuning, machine learning–based controller designed to efficiently account for the inherent high uncertainties in the robot’s operational environment at a reduced computational cost. Experimental and simulation-based tests were conducted under dynamic environments to validate the algorithm. Further, the ANADE was benchmarked against other recently developed navigation algorithms. Those tests were focused on the behaviour of the algorithm under challenging environments with moving and static obstacles and goals. Further, the test results demonstrate that the ANADE is successful in navigating robots under unknown, dynamically cluttered environments.
- Description: Doctor of Philosophy
Agoraphilic navigation algorithm in dynamic environment with and without prediction of moving objects location
- Hewawasam, Hasitha, Ibrahim, Yousef, Kahandawa, Gayan, Choudhury, Tanveer
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 Vol. 2019-October, p. 5179-5185
- Full Text:
- Reviewed:
- Description: 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 benched-marked with ANADE (Without predication) under similar environment conditions. From 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. © 2019 IEEE.
- Description: E1
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2019
- Type: Text , Conference proceedings , Conference paper
- Relation: 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019 Vol. 2019-October, p. 5179-5185
- Full Text:
- Reviewed:
- Description: 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 benched-marked with ANADE (Without predication) under similar environment conditions. From 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. © 2019 IEEE.
- Description: E1
Evaluating the Performances of the Agoraphilic Navigation Algorithm under Dead-Lock Situations
- Hewawasam, Hasitha, Ibrahim, Yousef, Kahandawa, Gayan, Choudhury, Tanveer
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th IEEE International Symposium on Industrial Electronics, ISIE 2020 Vol. 2020-June, p. 536-542
- Full Text:
- Reviewed:
- Description: 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 . 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 dead-lock (local minima) situations for APF method. The test results proved that the proposed algorithm has successfully eliminated the local minima problem of APF method. © 2020 IEEE.
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: 29th IEEE International Symposium on Industrial Electronics, ISIE 2020 Vol. 2020-June, p. 536-542
- Full Text:
- Reviewed:
- Description: 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 . 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 dead-lock (local minima) situations for APF method. The test results proved that the proposed algorithm has successfully eliminated the local minima problem of APF method. © 2020 IEEE.
Machine learning-based agoraphilic navigation algorithm for use in dynamic environments with a moving goal
- Hewawasam, Hasitha, Kahandawa, Gayan, Ibrahim, Yousef
- Authors: Hewawasam, Hasitha , Kahandawa, Gayan , Ibrahim, Yousef
- Date: 2023
- Type: Text , Journal article
- Relation: Machines Vol. 11, no. 5 (2023), p. 513
- Full Text:
- Reviewed:
- Description: This paper presents a novel development of a new machine learning-based control system for the Agoraphilic (free-space attraction) concept of navigating robots in unknown dynamic environments with a moving goal. Furthermore, this paper presents a new methodology to generate training and testing datasets to develop a machine learning-based module to improve the performances of Agoraphilic algorithms. The new algorithm presented in this paper utilises the free-space attraction (Agoraphilic) concept to safely navigate a mobile robot in a dynamically cluttered environment with a moving goal. The algorithm uses tracking and prediction strategies to estimate the position and velocity vectors of detected moving obstacles and the goal. This predictive methodology enables the algorithm to identify and incorporate potential future growing free-space passages towards the moving goal. This is supported by the new machine learning-based controller designed specifically to efficiently account for the high uncertainties inherent in the robot’s operational environment with a moving goal at a reduced computational cost. This paper also includes comparative and experimental results to demonstrate the improvements of the algorithm after introducing the machine learning technique. The presented experiments demonstrated the success of the algorithm in navigating robots in dynamic environments with the challenge of a moving goal.
- Authors: Hewawasam, Hasitha , Kahandawa, Gayan , Ibrahim, Yousef
- Date: 2023
- Type: Text , Journal article
- Relation: Machines Vol. 11, no. 5 (2023), p. 513
- Full Text:
- Reviewed:
- Description: This paper presents a novel development of a new machine learning-based control system for the Agoraphilic (free-space attraction) concept of navigating robots in unknown dynamic environments with a moving goal. Furthermore, this paper presents a new methodology to generate training and testing datasets to develop a machine learning-based module to improve the performances of Agoraphilic algorithms. The new algorithm presented in this paper utilises the free-space attraction (Agoraphilic) concept to safely navigate a mobile robot in a dynamically cluttered environment with a moving goal. The algorithm uses tracking and prediction strategies to estimate the position and velocity vectors of detected moving obstacles and the goal. This predictive methodology enables the algorithm to identify and incorporate potential future growing free-space passages towards the moving goal. This is supported by the new machine learning-based controller designed specifically to efficiently account for the high uncertainties inherent in the robot’s operational environment with a moving goal at a reduced computational cost. This paper also includes comparative and experimental results to demonstrate the improvements of the algorithm after introducing the machine learning technique. The presented experiments demonstrated the success of the algorithm in navigating robots in dynamic environments with the challenge of a moving goal.
The agoraphilic navigation algorithm under dynamic environment with a moving goal
- Hewawasam, Hasitha, Ibrahim, Yousef, Kahandawa, Gayan, Choudhury, Tanveer
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2021
- Type: Text , Conference paper
- Relation: 30th IEEE International Symposium on Industrial Electronics, ISIE 2021 Vol. 2021-June
- Full Text:
- Reviewed:
- Description: This paper presents a research conducted in developing a new navigation algorithm to navigate robots under dynamically cluttered environments with a moving goal. There are only a few navigation algorithms capable of navigating robots under dynamic environments compared to static environments. The inability to track and reach a moving goal/target is a one of the common weakness of existing navigating algorithms operating in dynamic environments. The existing free space attraction (Agoraphilic) based navigation algorithms also suffer from this common problem. The proposed algorithm, in this paper was developed to overcome this issue. Agoraphilic Navigation Algorithm under Dynamic Environment, 'ANADE' consists of eight main modules. These modules are iteratively used to create the robot's driving force which pulls the robot towards the moving goal. An obstacle tracking module is used to identify the time varying free spaces by tracking moving obstacles. Furthermore, a tracking system is also used to track the moving goal. The capacity of the ANADE was further strengthen by obstacle and goal path prediction modules. Future location prediction allowed the algorithm to make decision considering future environments around the robot. The proposed algorithm was tested under dynamic environment. These tests were focused on testing the behavior of the algorithm under the challenge of reaching a moving goal. Furthermore, the test results demonstrate that ANADE is successful in reaching a moving goal under an unknown dynamically cluttered environment. © 2021 IEEE.
- Authors: Hewawasam, Hasitha , Ibrahim, Yousef , Kahandawa, Gayan , Choudhury, Tanveer
- Date: 2021
- Type: Text , Conference paper
- Relation: 30th IEEE International Symposium on Industrial Electronics, ISIE 2021 Vol. 2021-June
- Full Text:
- Reviewed:
- Description: This paper presents a research conducted in developing a new navigation algorithm to navigate robots under dynamically cluttered environments with a moving goal. There are only a few navigation algorithms capable of navigating robots under dynamic environments compared to static environments. The inability to track and reach a moving goal/target is a one of the common weakness of existing navigating algorithms operating in dynamic environments. The existing free space attraction (Agoraphilic) based navigation algorithms also suffer from this common problem. The proposed algorithm, in this paper was developed to overcome this issue. Agoraphilic Navigation Algorithm under Dynamic Environment, 'ANADE' consists of eight main modules. These modules are iteratively used to create the robot's driving force which pulls the robot towards the moving goal. An obstacle tracking module is used to identify the time varying free spaces by tracking moving obstacles. Furthermore, a tracking system is also used to track the moving goal. The capacity of the ANADE was further strengthen by obstacle and goal path prediction modules. Future location prediction allowed the algorithm to make decision considering future environments around the robot. The proposed algorithm was tested under dynamic environment. These tests were focused on testing the behavior of the algorithm under the challenge of reaching a moving goal. Furthermore, the test results demonstrate that ANADE is successful in reaching a moving goal under an unknown dynamically cluttered environment. © 2021 IEEE.
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