Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

Kang, Jin Gu; Lim, Dong‐Woo; Choi, Yong-Sik; Jang, Won Il; Jung, Jin‐Woo

doi:10.20944/preprints202011.0494.v3

Cited by 7 publications

(12 citation statements)

References 4 publications

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“…The specification of the computer used in the simulation is shown in Table 1. The simulator used for the simulation [4] was developed based on C# WPF (Microsoft Visual Studio Community 2019 Version 16.1.6 Microsoft .NET Framework Version 4.8.03752), and only a single thread was used for calculations except for the visual part. generally, depending on the specification of the computer, the result of performance Measurement such as planning time may be variations during the simulation.…”

Section: Resultsmentioning

confidence: 99%

“…If it is free from collision, it calls postTriangular(), otherwise it calls interpolation(). postTriangular() connects qchild and qancestor like the Triangular Rewiring method [4], and the qparent between them is deleted from the path. interpolation() finds (interpolates) the point between qchild and qparent, and between qparent and qancestor that are free from obstacle collision when connected and rewire qchild, qancestor and those two points found.…”

Section: Endmentioning

confidence: 99%

“…The RRT algorithm and other sampling-based algorithms [3][4] offer the benefit of planning a path in a shorter time with less computing than traditional path planning algorithms like Visibility Graph-based [5], Cell Decomposition-based [6], and Potential Field-based [7]. On the other hand, it does not ensure optimality and has the drawback of being probabilistically assured completeness.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Enhancement Method of Rapidly-exploring Random Tree Robot Path Planning using Midpoint Interpolation

Kang¹,

Choi²,

Jung³

2021

Preprint

Self Cite

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To solve the problem that sampling-based Rapidly-exploring Random Tree (RRT) method is difficult to guarantee optimality. This paper proposed the Post Triangular Processing of Midpoint Interpolation method minimized the planning time and shorter path length of the sampling-based algorithm. The proposed Post Triangular Processing of Midpoint Interpolation method makes a closer to the optimal path and somewhat solves the sharp path problem through the interpolation process. The experiments were conducted to verify the performance of the proposed method. Applying the method proposed in this paper to the RRT algorithm increases the efficiency of optimization compared to the planning time.

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Section: Resultsmentioning

confidence: 99%

Section: Endmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Enhancement Method of Rapidly-exploring Random Tree Robot Path Planning using Midpoint Interpolation

Kang¹,

Choi²,

Jung³

2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The disinfection robot was designed using a path planning method called Rapidly-Exploring Random Tree Connect (RRT-Connect) [39], which consisted of two rapidly-exploring random trees (RRTs) and a simple greedy heuristic. RRTs were used for the robot's route planning, the aim of which was to select a route from a start position (qinit) to a goal position (qgoal), preventing the robot from colliding with a target object or obstacles.…”

Section: B Route Planningmentioning

confidence: 99%

A Smart Sterilization Robot System With Chlorine Dioxide for Spray Disinfection

et al. 2021

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The highly infectious and serious nature of coronavirus disease 2019 (COVID-19) has highlighted the need for hospital space disinfection technology and the prevention of human exposure to pathogenic environments. This research developed novel chlorine dioxide (ClO2) sterilization technology to reduce bacteria and viruses in the air and on surfaces. A smart sterilization robot system was also developed to spray disinfectants in operating theaters or patients' rooms, designed according to the results of controlled experiments and the requirements for hospital disinfection. The system was built incorporated a semi-automatic remote-controlled module and an automatic intelligent disinfection function; that is, it could operate independently according to specific epidemic prevention strategies, which were implemented using a combination of Internet of Things (IoT) applications and a gesture recognition function. The elimination of Escherichia coli (E. coli) bacteria on sample plates was 99.8 % effective. This paper reviews the evolution of various disinfection technologies and describes a disinfection robot system in detail.

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“…In order to solve the problem of path planning, a variety of tasks need to be completed, such as positioning, obstacle avoidance and so on. Some researchers put forward the research methods and development trend of robot path planning technology [6]. According to the degree of mastering environmental information, path planning of intelligent robot can be divided into global path planning based on model and local path planning based on sensor.…”

Section: Introductionmentioning

confidence: 99%

Application of an Improved Ant Colony Algorithm in Robot Path Planning and Mechanical Arm Management

2021

IJOMAM

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The purpose is to apply intelligent algorithm to the field of robot and improve the efficiency of robot path planning. First, ant colony algorithm in intelligent algorithm is expounded theoretically and computationally. On this basis, common particle swarm optimization algorithm is improved, and the improved ant colony algorithm calculation process is proposed. Finally, the simulation experiment of the robot with mechanical arm is carried out by Matrix Laboratory (MATLAB) software. The results show that the common ant colony algorithm can find the optimal path after 45 iterations, while the improved ant colony algorithm can find the optimal path after 25 iterations, which has faster convergence speed and shorter path length. There is a certain error between the actual trajectory of the mechanical arm on X-Y axis, X-Z axis, Y-Z axis and X-Y-Z axis and the ideal trajectory planned by the algorithm, and the error is about 2mm. Under random terrain conditions and U-shaped obstacle terrain conditions, the robot path planning result based on the improved ant colony algorithm is the shortest and the condition is the best; however, the robot path under the improved ant colony algorithm is reduced by about 3cm and 13cm compared with the common ant colony algorithm, and the optimal iteration times are reduced by 20 and 38 times, respectively. It shows that the improved ant colony algorithm can make the robot with mechanical arm explore the optimal and shortest path in a short time. Although there are some errors between the trajectory of the mechanical arm with the ideal trajectory, the errors are in the controllable range, that is, the improved ant colony algorithm has high efficiency.

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Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

Cited by 7 publications

References 4 publications

An Enhancement Method of Rapidly-exploring Random Tree Robot Path Planning using Midpoint Interpolation

An Enhancement Method of Rapidly-exploring Random Tree Robot Path Planning using Midpoint Interpolation

A Smart Sterilization Robot System With Chlorine Dioxide for Spray Disinfection

Application of an Improved Ant Colony Algorithm in Robot Path Planning and Mechanical Arm Management

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