Modified Headed Social Force Model Based on Hybrid Velocity Obstacles for Mobile Robot to Avoid Disturbed Groups of Pedestrians

Fuad, Muhammad; Agustinah, Trihastuti; Purwanto, Djoko

doi:10.22266/ijies2021.0630.20

Cited by 10 publications

(7 citation statements)

References 12 publications

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“…Although this algorithm can maintain human safety around the robot, additional capabilities are still needed to maintain human comfort so that the robot can operate in the human environment properly. Some approaches that take into account the comfort side of human psychology were studied in [10] and [11]. Research [12] examined collision-avoidance on an Unmanned Aerial Vehicle (UAV) in a condition known as Suicidal Pedestrian Game (SPG).…”

Section: Navigation Can Maintain Both Of These Factors With the Support Of Collision-avoidancementioning

confidence: 99%

“…Several studies considered keeping the comfort of individual pedestrian [7] and [9]. Other studies included the comfort of a group of pedestrians as their objectives, such as examined in [10] and [11]. In general, these studies had the assumption that the velocity of pedestrians is always constant except in [11].…”

Section: Navigation Can Maintain Both Of These Factors With the Support Of Collision-avoidancementioning

confidence: 99%

“…Although the robot has to evade the pursuer and avoid human obstacles, it must maintain the safety and comfort of humans while it navigates from initial to target position. This research uses TLI [11] as a standard of safety and comfort distance.…”

Section: Proposed Path-velocity Plannermentioning

confidence: 99%

“…The desired velocity used to be defined by giving a certain value or by adjusting to a random number [10]. This research proposes to utilize HVO in [11] to generate the desired velocity based on LIDAR scan on robot surrounding as described as follows:…”

Section: Proposed Collision-avoidancementioning

confidence: 99%

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Evading of Pedestrian Pursuer and Avoiding Obstacles Using Path-Velocity Planner

et al. 2021

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The ability to navigate mobile robot from initial to target position while maintaining the safety and comfort of pedestrian have to be supported by a collision-avoidance system. In the case of pursuit-evasion when a pedestrian pursues a robot, navigation must be able to evade capture from the pursuer. This paper aims to improve the collision-avoidance method based on Hybrid Velocity Obstacles (HVO) concerning the pursuer. This paper proposes a path-velocity planner that consists of a global path planner, and two velocity planners. These velocity planners combine pure pursuit path following and proposed collision-avoidance method. This research presents a modified version of the Headed Social Force Model (MHSFM) based on modified HVO (MHVO). The linear velocity of MHVO is employed to generate the MHSFM target force. The interaction force of MHSFM is influenced by static and moving objects, and pursuers. The angular velocity of MHVO is used to steer the robot away from the pursuer. This proposed method was evaluated with two simulation scenarios. MHVO-based MHSFM was implemented into a two-wheeled differentialsteering mobile robot that navigated in an indoor human environment. The results show that the proposed method is capable to evade a pedestrian pursuer by maintaining the safety and comfort of other pedestrians with an average value of 0.25 on the Threat Level Index (TLI).INDEX TERMS Collision-avoidance, differential-steering mobile robot, modified headed social force model, modified hybrid velocity obstacles, pedestrian pursuer, path-velocity planner.

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Section: Navigation Can Maintain Both Of These Factors With the Support Of Collision-avoidancementioning

confidence: 99%

Section: Navigation Can Maintain Both Of These Factors With the Support Of Collision-avoidancementioning

confidence: 99%

Section: Proposed Path-velocity Plannermentioning

confidence: 99%

Section: Proposed Collision-avoidancementioning

confidence: 99%

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Evading of Pedestrian Pursuer and Avoiding Obstacles Using Path-Velocity Planner

et al. 2021

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“…Random paths of mobile robot, single pedestrian, and group of pedestrians were created by used probabilistic roadmap (PRM). The disadvantage of using (PRM) is not giving the optimal solution every time [13].…”

Section: Introductionmentioning

confidence: 99%

Static and Dynamic Path Planning Algorithms Design for a Wheeled Mobile Robot Based on a Hybrid Technique

2022

IJIES

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During the previous years, the number of researchers who discussed the field of path planning algorithms has increased. In this paper, a proposed hybrid technique for path planning based on the benefits of sampling-based algorithms and heuristic path planning algorithms was enhanced. Rapidly-exploring Random Tree star (RRT*) was used to generate the candidate nodes that represent a collision-free path. These candidate nodes were applied to the Particle Swarm Optimization (PSO) algorithm to generate the shortest and the smoothest path planning (the optimal path planning) for the mobile robot. The RRT*PSO algorithm was applied in two scenarios (static and dynamic environments) with a workspace of [500×500] cm using MATLAB 2021a. In the static environment, a workspace full of obstacles was chosen to find the shortest collision-free path. In addition, a reference path equation was found to calculate the reference linear and angular velocities of the mobile robot as well as the linear and angular velocities of the right and left wheels. In this work, the suggested hybrid RRT*PSO algorithm improves path length 34.27% compared to the A* algorithm and the fuzzy analytic hierarchy process (A*-FAHP hybrid) algorithm and 0.35% compared to the Self-adaptive evolutionary game-based particle swarm optimization (SAEGBPSO) algorithm. In the dynamic environment, an algorithm named (contour path down and contour path up) was suggested to avoid collisions with dynamic obstacles. By using this suggested algorithm, the reference linear and angular velocities of the mobile robot as well as the linear and angular velocities of the right and left wheels were calculated to obtain a smooth path followed and free-navigation with dynamic obstacles in an environment.

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Virtual-leader Split/Rejoin-based Flocking Control With Obstacle Avoidance for Multi-agents

Wu,

Ji,

Sun

et al. 2024

Int. J. Control Autom. Syst.

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Modified Headed Social Force Model Based on Hybrid Velocity Obstacles for Mobile Robot to Avoid Disturbed Groups of Pedestrians

Cited by 10 publications

References 12 publications

Evading of Pedestrian Pursuer and Avoiding Obstacles Using Path-Velocity Planner

Evading of Pedestrian Pursuer and Avoiding Obstacles Using Path-Velocity Planner

Static and Dynamic Path Planning Algorithms Design for a Wheeled Mobile Robot Based on a Hybrid Technique

Virtual-leader Split/Rejoin-based Flocking Control With Obstacle Avoidance for Multi-agents

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