Search results

1 – 10 of over 60000
To view the access options for this content please click here
Article
Publication date: 9 January 2009

Heping Chen, Thomas Fuhlbrigge and Xiongzi Li

Paint path planning for industrial robots is critical for uniform paint distribution, process cycle time and material waste, etc. However, paint path planning is still a…

Downloads
1781

Abstract

Purpose

Paint path planning for industrial robots is critical for uniform paint distribution, process cycle time and material waste, etc. However, paint path planning is still a costly and time‐consuming process. Currently paint path planning has always caused a bottle‐neck for manufacturing automation because typical manual teaching methods are tedious, error‐prone and skill‐dependent. Hence, it is essential to develop automated tool pathplanning methods to replace manual paint path planning. The purpose of this paper is to review the existing automated tool pathplanning methods, and investigate their advantages and disadvantages.

Design/methodology/approach

The approach takes the form of a review of automated tool pathplanning methods, to investigate the advantages and disadvantages of the current technologies.

Findings

Paint path planning is a very complicated task considering complex parts, paint process requirements and complicated spraying tools. There are some research and development efforts in this area. Based on the review of the methods used for paint path planning and simulation, the paper concludes that: the tessellated CAD model formats have many advantages in paint path planning and paint deposition simulation. However, the tessellated CAD model formats lack edge and connection information. Hence, it may not be suitable for some applications requiring edge following, such as welding. For the spray gun model, more complicated models, such as 2D models, should be used for both path planning and paint distribution simulation. Paint path generation methods should be able to generate a paint path for complex automotive parts without assumptions, such as presupposing a part with a continuous surface.

Practical implications

The paper makes possible automated path generation for spray‐painting process using industrial robots such that the pathplanning time can be reduced, the product quality improved, etc.

Originality/value

The paper provides a useful review of current paint pathplanning methodologies based on the CAD models of parts.

Details

Industrial Robot: An International Journal, vol. 36 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 11 July 2018

Zhaotian Wang, Yezhuo Li and Yan-An Yao

The purpose of this paper is to put forward a rolling assistant robot with two rolling modes, and the multi-mode rolling motion strategy with path planning algorithm…

Abstract

Purpose

The purpose of this paper is to put forward a rolling assistant robot with two rolling modes, and the multi-mode rolling motion strategy with path planning algorithm, which is suitable to this multi-mode mobile robot, is proposed based on chessboard-shaped grid division (CGD).

Design/methodology/approach

Based on the kinematic analysis and motion properties of the mobile parallel robot, the motion strategy based on CGD path planning algorithm of a mobile robot with two rolling modes moving to a target position is divided into two parts, which are local self-motion planning and global path planning. In the first part, the mobile parallel robot can move by switching and combining the two rolling modes; and in the second part, the specific algorithm of the global path planning is proposed according to the CGD of the moving ground.

Findings

The assistant robot, which is a novel 4-RSR mobile parallel robot (where R denotes a revolute joint and S denotes a spherical joint) integrating operation and rolling locomotion (Watt linkage rolling mode and 6R linkage rolling mode), can work as a moving spotlight or worktable. A series of simulation and prototype experiment results are presented to verify the CGD path planning strategy of the robot, and the performance of the path planning experiments in simulations and practices shows the validation of the path planning analysis.

Originality/value

The work presented in this paper is a further exploration to apply parallel mechanisms with two rolling modes to the field of assistant rolling robots by proposing the CGD path planning strategy. It is also a new attempt to use the specific path planning algorithm in the field of mobile robots for operating tasks.

Details

Industrial Robot: An International Journal, vol. 45 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 26 September 2019

Ruochen Tai, Jingchuan Wang and Weidong Chen

In the running of multiple automated guided vehicles (AGVs) in warehouses, delay problems in motions happen unavoidably as there might exist some disabled components of…

Abstract

Purpose

In the running of multiple automated guided vehicles (AGVs) in warehouses, delay problems in motions happen unavoidably as there might exist some disabled components of robots, the instability of networks and the interference of people walking. Under this case, robots would not follow the designed paths and the coupled relationship between temporal and space domain for paths is broken. And there is no doubt that other robots are disturbed by the ones where delays happen. Finally, this brings about chaos or even breakdown of the whole system. Therefore, taking the delay disturbance into consideration in the path planning of multiple robots is an issue worthy of attention and research.

Design/methodology/approach

This paper proposes a prioritized path planning algorithm based on time windows to solve the delay problems of multiple AGVs. The architecture is a unity consisting of three components which are focused on scheduling AGVs under normal operations, delays of AGVs, and recovery of AGVs. In the components of scheduling AGVs under normal operations and recovery, this paper adopts a dynamic routing method based on time windows to ensure the coordination of multiple AGVs and efficient completion of tasks. In the component for scheduling AGVs under delays, a dynamical prioritized local path planning algorithm based on time windows is designed to solve delay problems. The introduced planning principle of time windows would enable the algorithm to plan new solutions of trajectories for multiple AGVs, which could lower the makespan. At the same time, the real-time performance is acceptable based on the planning principle which stipulates the parameters of local time windows to ensure that the computation of the designed algorithm would not be too large.

Findings

The simulation results demonstrate that the proposed algorithm is more efficient than the state-of-the-art method based on homotopy classes, which aims at solving the delay problems. What is more, it is validated that the proposed algorithm can achieve the acceptable real-time performance for the scheduling in warehousing applications.

Originality/value

By introducing the planning principle and generating delay space and local adjustable paths, the proposed algorithm in this paper can not only solve the delay problems in real time, but also lower the makespan compared with the previous method. The designed algorithm guarantees the scheduling of multiple AGVs with delay disturbance and enhances the robustness of the scheduling algorithm in multi-AGV system.

Details

Assembly Automation, vol. 39 no. 5
Type: Research Article
ISSN: 0144-5154

Keywords

To view the access options for this content please click here
Article
Publication date: 14 October 2021

Tianying Xu, Haibo Zhou, Shuaixia Tan, Zhiqiang Li, Xia Ju and Yichang Peng

This paper aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense…

Abstract

Purpose

This paper aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.

Design/methodology/approach

In this paper, an improved artificial potential field method is proposed, where the object can leave the local minima point, where the algorithm falls into, while it avoids the obstacle, following a shorter feasible path along the repulsive equipotential surface, which is locally optimized. The whole obstacle avoidance process is based on the improved artificial potential field method, applied during the mechanical arm path planning action, along the motion from the starting point to the target point.

Findings

Simulation results show that the algorithm in this paper can effectively perceive the obstacle shape in all the selected cases and can effectively shorten the distance of the planned path by 13%–41% with significantly higher planning efficiency compared with the improved artificial potential field method based on rapidly-exploring random tree. The experimental results show that the improved artificial potential field method can effectively plan a smooth collision-free path for the object, based on an algorithm with good environmental adaptability.

Originality/value

An improved artificial potential field method is proposed for optimized obstacle avoidance path planning of a mechanical arm in three-dimensional space. This new approach aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 18 May 2020

Haojie Zhang, Yudong Zhang and Tiantian Yang

As wheeled mobile robots find increasing use in outdoor applications, it becomes more important to reduce energy consumption to perform more missions efficiently with…

Abstract

Purpose

As wheeled mobile robots find increasing use in outdoor applications, it becomes more important to reduce energy consumption to perform more missions efficiently with limit energy supply. The purpose of this paper is to survey the current state-of-the-art on energy-efficient motion planning (EEMP) for wheeled mobile robots.

Design/methodology/approach

The use of wheeled mobile robots has been increased to replace humans in performing risky missions in outdoor applications, and the requirement of motion planning with efficient energy consumption is necessary. This study analyses a lot of motion planning technologies in terms of energy efficiency for wheeled mobile robots from 2000 to present. The dynamic constraints play a key role in EEMP problem, which derive the power model related to energy consumption. The surveyed approaches differ in the used steering mechanisms for wheeled mobile robots, in assumptions on the structure of the environment and in computational requirements. The comparison among different EEMP methods is proposed in optimal, computation time and completeness.

Findings

According to lots of literature in EEMP problem, the research results can be roughly divided into online real-time optimization and offline optimization. The energy consumption is considered during online real-time optimization, which is computationally expensive and time-consuming. The energy consumption model is used to evaluate the candidate motions offline and to obtain the optimal energy consumption motion. Sometimes, this optimization method may cause local minimal problem and even fail to track. Therefore, integrating the energy consumption model into the online motion planning will be the research trend of EEMP problem, and more comprehensive approach to EEMP problem is presented.

Research limitations/implications

EEMP is closely related to robot’s dynamic constraints. This paper mainly surveyed in EEMP problem for differential steered, Ackermann-steered, skid-steered and omni-directional steered robots. Other steering mechanisms of wheeled mobile robots are not discussed in this study.

Practical implications

The survey of performance of various EEMP serves as a reference for robots with different steering mechanisms using in special scenarios.

Originality/value

This paper analyses a lot of motion planning technologies in terms of energy efficiency for wheeled mobile robots from 2000 to present.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 14 June 2013

Yang Gao, Shu‐dong Sun, Da‐wei Hu and Lai‐jun Wang

Path planning in unknown or partly unknown environment is a quite complex task, partly because it is an evolving globally optimal path affected by the motion of the robot…

Abstract

Purpose

Path planning in unknown or partly unknown environment is a quite complex task, partly because it is an evolving globally optimal path affected by the motion of the robot and the changing of environmental information. The purpose of this paper is to propose an online path planning approach for a mobile robot, which aims to provide a better adaptability to the motion of the robot and the changing of environmental information.

Design/methodology/approach

This approach treats the globally optimal path as a changing state and estimates it online with two steps: prediction step, which predicts the globally optimal path based on the motion of the robot; and updating step, which uses the up‐to‐date environmental information to refine the prediction.

Findings

Simulations and experiments show that this approach needs less time to reach the destination than some classical algorithms, provides speedy convergence and can adapt to unexpected obstacles or very limited prior environmental information. The better performances of this approach have been proved in both field and indoor environments.

Originality/value

Compared with previous works, the paper's approach has three main contributions. First, it can reduce the time consumed in reaching the destination by adopting an online path planning strategy. Second, it can be applied in such environments as those with unexpected obstacles or with only limited prior environmental information. Third, both motion error of the robot and the changing of environmental information are considered, so that the global adaptability to them is improved.

Details

Industrial Robot: An International Journal, vol. 40 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 1 October 1994

Stephen Cameron

Outlines the state‐of‐the‐art in obstacle avoidanceand path planning for industrial robots that is practical on the currentgeneration of computer hardware. Describes…

Downloads
583

Abstract

Outlines the state‐of‐the‐art in obstacle avoidance and path planning for industrial robots that is practical on the current generation of computer hardware. Describes practical vehicle planners and planning for manipulators. Summarizes that obstacle avoidance and path planning are techniques with differing goals. Sonar is the standard method of obstacle avoidance systems which is largely limited by the reliability of the sensors used. Path planning however is limited by two things: the algorithms used and the quality of the data available to planners. Concludes that it is now possible to produce path planning and obstacle avoidance systems that can be used in practical robotic systems.

Details

Industrial Robot: An International Journal, vol. 21 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 8 July 2020

Wichai Pawgasame and Komwut Wipusitwarakun

The border control becomes challenging when a protected region is large and there is a limited number of border patrols. This research paper proposes a novel…

Abstract

Purpose

The border control becomes challenging when a protected region is large and there is a limited number of border patrols. This research paper proposes a novel heuristic-based patrol path planning scheme in order to efficiently patrol with resource scarcity.

Design/methodology/approach

The trespasser influencing score, which is determined from the environmental characteristics and trespassing statistic of the region, is used as a heuristic for measuring a chance of approaching a trespasser. The patrol plan is occasionally updated with a new trespassing statistic during a border operation. The performance of the proposed patrol path planning scheme was evaluated and compared with other patrol path planning schemes by the empirical experiment under different scenarios.

Findings

The result from the experiment indicates that the proposed patrol planning outperforms other patrol path planning schemes in terms of the trespasser detection rate, when more environment-aware trespassers are in the region.

Research limitations/implications

The experiment was conducted through simulated agents in simulated environment, which were assumed to mimic real behavior and environment.

Originality/value

This research paper contributes a heuristic-based patrol path planning scheme that applies the environmental characteristics and dynamic statistic of the region, as well as a border surveillance problem model that would be useful for mobile sensor planning in a border surveillance application.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 13 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

To view the access options for this content please click here
Article
Publication date: 18 January 2016

Shaorong Xie, Peng Wu, Hengli Liu, Peng Yan, Xiaomao Li, Jun Luo and Qingmei Li

This paper aims to propose a new method for combining global path planning with local path planning, to provide an efficient solution for unmanned surface vehicle (USV…

Abstract

Purpose

This paper aims to propose a new method for combining global path planning with local path planning, to provide an efficient solution for unmanned surface vehicle (USV) path planning despite the changeable environment. Path planning is the key issue of USV navigation. A lot of research works were done on the global and local path planning. However, little attention was given to combining global path planning with local path planning.

Design/methodology/approach

A search of shortcut Dijkstra algorithm was used to control the USV in the global path planning. When the USV encounters unknown obstacles, it switches to our modified artificial potential field (APF) algorithm for local path planning. The combinatorial method improves the approach of USV path planning in complex environment.

Findings

The method in this paper offers a solution to the issue of path planning in changeable or unchangeable environment, and was confirmed by simulations and experiments. The USV follows the global path based on the search of shortcut Dijkstra algorithm. Both USV achieves obstacle avoidances in the local region based on the modified APF algorithm after obstacle detection. Both the simulation and experimental results demonstrate that the combinatorial path planning method is more efficient in the complex environment.

Originality/value

This paper proposes a new path planning method for USV in changeable environment. The proposed method is capable of efficient navigation in changeable and unchangeable environment.

Details

Industrial Robot: An International Journal, vol. 43 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

To view the access options for this content please click here
Article
Publication date: 15 June 2010

Jianming Guo and Liang Liu

The purpose of this paper is to improve the D* algorithm which has been used usually in robotics for mobile robot navigation in unknown or dynamic environments.

Abstract

Purpose

The purpose of this paper is to improve the D* algorithm which has been used usually in robotics for mobile robot navigation in unknown or dynamic environments.

Design/methodology/approach

First, the model of 2D workspace with some obstacles is expressed in regularity grids. The optimal path is planned by using the improved D* algorithm by searching in the neighbor grid cells in 16 directions. It makes the robot that the smallest turning angle drops to π/8. The robot moving angle discrete precision is raised and the unnecessary cost of path planning is reduced so the robot motion path is smoother. Then, the improved D* algorithm is simulated in MOBOTSIM software environment and is tested by the WiRobotX80 mobile robot.

Findings

To search in the neighbor grid cells in 16 directions instead of eight directions by using D* algorithms for path planning.

Research limitations/implications

The map should be expressed in regularity grids.

Originality/value

The improved D* algorithm is effective and it can result in a higher quality path than the conventional D* algorithm at the same map environment.

Details

Kybernetes, vol. 39 no. 6
Type: Research Article
ISSN: 0368-492X

Keywords

1 – 10 of over 60000