RETRACTED: Path planning for autonomous robots – a comprehensive analysis by a greedy algorithm

Shih, Bih-Yaw; Chang, Hsiang; Chen, Chen-Yuan

doi:10.1177/1077546311429841

Cited by 14 publications

(4 citation statements)

References 107 publications

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“…The length of the segment is calculated by applying Euclidean distance between points. The Euclidean distance between two points, 𝑝 1 = (𝑥 1 , 𝑦 1 ) and 𝑝 2 = (𝑥 2 , 𝑦 2 ), can be calculated in (1).…”

Section: Path Lengthmentioning

confidence: 99%

“…A lot of research has been done on this problem in robotics. PP is defined as the process of determining the best feasible path that allows mobile robots to move from a starting point to a target point of the environment before they move, which is considered the main problem in robot navigation [1]. There are three types of environments in the field of autonomous path planning for mobile robots: static environments with fixed obstacles, dynamic environments with movable obstacles, and dynamic environments with movable obstacles and the target point at the same time.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid approach for multi-objective optimization path planning with moving target

Abed

Jasim

2022

IJEECS

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Path planning algorithms are the most significant area in the robotics field. Path planning (PP) can be defined as the process of determining the most appropriate navigation path before a mobile robot moves. Path planning optimization refers to finding the optimal or near-optimal path. Multi-objective optimization (MOO) is concerned with finding the best solution values that satisfy multiple objectives, such as shortness, smoothness, and safety. MOO present the challenge of making decisions while balancing these contradictory issues through compromise (tradeoff). As a result, there is no single solution appropriate for all purposes in MOO, but rather a range of solutions. Several objectives are considered as part of this study, including path security, length, and smoothness, when planning paths for autonomous mobile robots in a dynamic environment with a moving target. Particle swarm optimization (PSO) algorithms are combined with bat algorithms (BA) to make a balance between exploration and exploitation. PSO algorithms used to optimize two important parameters of the bat algorithm. The proposed solution is tested through several simulations based on varying scenarios. The results demonstrate that mobile robots can travel clearly and safely along short paths and smoothly, proving this method's efficiency.

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Section: Path Lengthmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid approach for multi-objective optimization path planning with moving target

Abed

Jasim

2022

IJEECS

View full text Add to dashboard Cite

show abstract

“…In robot navigation, the main problem is to calculate a feasible path from a starting to a target point of the environment. This problem is known as path planning (PP) problem (Shih et al 2013). Currently, PP is one of the most researched topics in the field of robotics.…”

Section: Introductionmentioning

confidence: 99%

Solving the multi-objective path planning problem in mobile robotics with a firefly-based approach

et al. 2015

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Currently, autonomous robotics is one of the most interesting and researched areas of technology. At the beginning, robots only worked in the industrial sector but, gradually, they started to be introduced into other sectors such as medicine or social environments becoming part of society. In mobile robots, the path planning (PP) problem is one of the most researched topics. Taking into account that the PP problem is an NP-hard problem, multi-objective evolutionary algorithms (MOEAs) are good candidates to solve this problem. In this work, a new multi-objective approach based on the flashing behavior of fireflies in nature, the multi-objective firefly algorithm (MO-FA), is proposed to solve the PP problem. This proposed algorithm is a swarm intelligence algorithm. The proposed MO-FA handles three different objectives to obtain accurate and efficient solutions. These objectives are the following: the path safety, the path length, and the path smoothness (related to the energy conCommunicated by sumption). Furthermore, and to test the proposed MOEA, we have used eight realistic scenarios for the path's calculation. On the other hand, we also compare our proposal with other approaches of the state of the art, showing the advantages of MO-FA. In particular, to evaluate the obtained results we applied specific quality metrics. Moreover, to demonstrate the statistical evidence of the obtained results, we also performed a statistical analysis. Finally, the study shows that the proposed MO-FA is a good alternative to solve the PP problem.

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“…There are different methods and algorithms which are used by parallel robots to generate the motion, such as Probabilistic Roadmap, Lightning method, and Greedy algorithm, while singularity points of the work space will be considered for developing and creating the motions. 20,21 The ankle bone is one of the most complex structures in the body and ankle sprains are one of the most prevalent problems for the ankle. Quick rehabilitation may reduce the risk of repeating these sprains.…”

Section: Introductionmentioning

confidence: 99%

Path planning of the hybrid parallel robot for ankle rehabilitation

et al. 2014

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SUMMARYThis paper presents a new configuration for ankle rehabilitation using a 9-DOF (degree of freedom) hybrid parallel robot. The robot contains nine linear actuators serially connecting two movable platforms and one stationary platform. The optimization is based on the singularity and dynamic analysis of the robot. The obtained data of the ankle motions from a series of experiments were applied to the model in order to investigate the motion of the end-effector and the force required for each actuator in a particular path. The end-effector tracking simulation results validated the proposed theoretical analysis of the required rehabilitation path of the foot.

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RETRACTED: Path planning for autonomous robots – a comprehensive analysis by a greedy algorithm

Cited by 14 publications

References 107 publications

Hybrid approach for multi-objective optimization path planning with moving target

Hybrid approach for multi-objective optimization path planning with moving target

Solving the multi-objective path planning problem in mobile robotics with a firefly-based approach

Path planning of the hybrid parallel robot for ankle rehabilitation

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