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Article
Publication date: 6 January 2012

Biyun Xie, Jing Zhao and Yu Liu

The purpose of this paper is to present a new nested rapidly‐exploring random tree (RRT) algorithm for fault tolerant motion planning of robotic manipulators.

Abstract

Purpose

The purpose of this paper is to present a new nested rapidly‐exploring random tree (RRT) algorithm for fault tolerant motion planning of robotic manipulators.

Design/methodology/approach

Another RRT algorithm is nested within the general RRT algorithm. This second nested level is used to check whether the new sampled node in the first nested level is fault tolerant. If a solution can be found in the second nested RRT, the reduced manipulator after failures at the new sampled node can still fulfill the remaining task and this new sampled node is added into the nodes of RRT in the first level. Thus, the nodes in the first level RRT algorithm are all fault tolerant postures. The final trajectory joined by these nodes is also obviously fault tolerant. Besides fault tolerance, this new nested RRT algorithm also can fulfill some secondary tasks such as improvement of dexterity and obstacle avoidance. Sufficient simulations and experiments of this new algorithm on fault tolerant motion planning of robotic manipulators are implemented.

Findings

It is found that the new nested RRT algorithm can fulfill fault tolerance and some other secondary tasks at the same time. Compared to other existing fault tolerant algorithms, this new algorithm is more efficient.

Originality/value

The paper presents a new nested RRT algorithm for fault tolerant motion planning.

Details

Industrial Robot: An International Journal, vol. 39 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 11 July 2023

Yuze Shang, Fei Liu, Ping Qin, Zhizhong Guo and Zhe Li

The goal of this research is to develop a dynamic step path planning algorithm based on the rapidly exploring random tree (RRT) algorithm that combines Q-learning with the…

Abstract

Purpose

The goal of this research is to develop a dynamic step path planning algorithm based on the rapidly exploring random tree (RRT) algorithm that combines Q-learning with the Gaussian distribution of obstacles. A route for autonomous vehicles may be swiftly created using this algorithm.

Design/methodology/approach

The path planning issue is divided into three key steps by the authors. First, the tree expansion is sped up by the dynamic step size using a combination of Q-learning and the Gaussian distribution of obstacles. The invalid nodes are then removed from the initially created pathways using bidirectional pruning. B-splines are then employed to smooth the predicted pathways.

Findings

The algorithm is validated using simulations on straight and curved highways, respectively. The results show that the approach can provide a smooth, safe route that complies with vehicle motion laws.

Originality/value

An improved RRT algorithm based on Q-learning and obstacle Gaussian distribution (QGD-RRT) is proposed for the path planning of self-driving vehicles. Unlike previous methods, the authors use Q-learning to steer the tree's development direction. After that, the step size is dynamically altered following the density of the obstacle distribution to produce the initial path rapidly and cut down on planning time even further. In the aim to provide a smooth and secure path that complies with the vehicle kinematic and dynamical restrictions, the path is lastly optimized using an enhanced bidirectional pruning technique.

Details

Engineering Computations, vol. 40 no. 5
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 7 August 2017

Du Lin, Bo Shen, Yurong Liu, Fuad E. Alsaadi and Ahmed Alsaedi

The purpose of this paper is to improve the performance of the genetic algorithm-based compliant robot path planning (GACRPP) in complex dynamic environment by proposing an…

Abstract

Purpose

The purpose of this paper is to improve the performance of the genetic algorithm-based compliant robot path planning (GACRPP) in complex dynamic environment by proposing an improved bidirectional rapidly exploring random tree (Bi-RRT)-based population initialization method.

Design/methodology/approach

To achieve GACRPP in complex dynamic environment with high performance, an improved Bi-RRT-based population initialization method is proposed. First, the grid model is adopted to preprocess the working space of mobile robot. Second, an improved Bi-RRT is proposed to create multi-cluster connections between the starting point and the goal point. Third, the backtracking method is used to generate the initial population based on the multi-cluster connections generated by the improved Bi-RRT. Subsequently, some comparative experiments are implemented where the performances of the improved Bi-RRT-based population initialization method are compared with other population initialization methods, and the comparison results of the improved genetic algorithm (IGA) combining with the different population initialization methods are shown. Finally, the optimal path is further smoothed with the help of the technique of quadratic B-spline curves.

Findings

It is shown in the experiment results that the improved Bi-RRT-based population initialization method is capable of deriving a more diversified initial population with less execution time and the IGA combining with the proposed population initialization method outperforms the one with other population initialization methods in terms of the length of optimal path and the execution time.

Originality/value

In this paper, the Bi-RRT is introduced as a population initialization method into the GACRPP problem. An improved Bi-RRT is proposed for the purpose of increasing the diversity of initial population. To characterize the diversity of initial population, a new notion of breadth is defined in terms of Hausdorff distance between different paths.

Details

Assembly Automation, vol. 37 no. 3
Type: Research Article
ISSN: 0144-5154

Keywords

Article
Publication date: 20 June 2016

Nino Pereira, A.Fernando Ribeiro, Gil Lopes and Jorge Lino

The purpose of this paper is to characterise the TWIN-RRT* algorithm which solves a motion planning problem in which an agent has multiple possible targets where none of them is…

281

Abstract

Purpose

The purpose of this paper is to characterise the TWIN-RRT* algorithm which solves a motion planning problem in which an agent has multiple possible targets where none of them is compulsory and retrieves feasible, “low cost”, asymptotically optimal and probabilistically complete paths. The TWIN-RRT* algorithm solves path planning problems for both holonomic and non-holonomic robots with or without kinematic constraints in a 2D environment.

Design/methodology/approach

It was designed to work equally well with higher degree of freedom agents in different applications. It provides a practical implementation of feasible and fast planning, namely where a closed loop is required. Initial and final configurations are allowed to be exactly the same.

Findings

The TWIN-RRT* algorithm computes an efficient path for a single agent towards multiple targets where none of them is mandatory. It inherits the low computational cost, probabilistic completeness and asymptotical optimality from RRT*.

Research limitations/implications

It uses efficiency as cost function, which can be adjusted to the requirements of any given application. TWIN-RRT also shows compliance with kinematic constraints.

Practical implications

The practical application where this work has been used consists of an autonomous mobile robot that picks up golf balls in a driving range. The multiple targets are the golf balls and the optimum path is a requirement to reduce the time and energy to refill as quickly as possible the balls dispensing machine.

Originality/value

The new random sampling algorithm – TWIN-RRT* – is able to generate feasible efficient paths towards multiple targets retrieving closed-loop paths starting and finishing at the same configuration.

Details

Industrial Robot: An International Journal, vol. 43 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 8 May 2024

Minghao Wang, Ming Cong, Yu Du, Huageng Zhong and Dong Liu

To make the robot that have real autonomous ability is always the goal of mobile robot research. For mobile robots, simultaneous localization and mapping (SLAM) research is no…

Abstract

Purpose

To make the robot that have real autonomous ability is always the goal of mobile robot research. For mobile robots, simultaneous localization and mapping (SLAM) research is no longer satisfied with enabling robots to build maps by remote control, more needs will focus on the autonomous exploration of unknown areas, which refer to the low light, complex spatial features and a series of unstructured environment, lick underground special space (dark and multiintersection). This study aims to propose a novel robot structure with mapping and autonomous exploration algorithms. The experiment proves the detection ability of the robot.

Design/methodology/approach

A small bio-inspired mobile robot suitable for underground special space (dark and multiintersection) is designed, and the control system is set up based on STM32 and Jetson Nano. The robot is equipped with double laser sensor and Ackerman chassis structure, which can adapt to the practical requirements of exploration in underground special space. Based on the graph optimization SLAM method, an optimization method for map construction is proposed. The Iterative Closest Point (ICP) algorithm is used to match two frames of laser to recalculate the relative pose of the robot, which improves the sensor utilization rate of the robot in underground space and also increase the synchronous positioning accuracy. Moreover, based on boundary cells and rapidly-exploring random tree (RRT) algorithm, a new Bio-RRT method for robot autonomous exploration is proposed in addition.

Findings

According to the experimental results, it can be seen that the upgraded SLAM method proposed in this paper achieves better results in map construction. At the same time, the algorithm presents good real-time performance as well as high accuracy and strong maintainability, particularly it can update the map continuously with the passing of time and ensure the positioning accuracy in the process of map updating. The Bio-RRT method fused with the firing excitation mechanism of boundary cells has a more purposeful random tree growth. The number of random tree expansion nodes is less, and the amount of information to be processed is reduced, which leads to the path planning time shorter and the efficiency higher. In addition, the target bias makes the random tree grow directly toward the target point with a certain probability, and the obtained path nodes are basically distributed on or on both sides of the line between the initial point and the target point, which makes the path length shorter and reduces the moving cost of the mobile robot. The final experimental results demonstrate that the proposed upgraded SLAM and Bio-RRT methods can better complete the underground special space exploration task.

Originality/value

Based on the background of robot autonomous exploration in underground special space, a new bio-inspired mobile robot structure with mapping and autonomous exploration algorithm is proposed in this paper. The robot structure is constructed, and the perceptual unit, control unit, driving unit and communication unit are described in detail. The robot can satisfy the practical requirements of exploring the underground dark and multiintersection space. Then, the upgraded graph optimization laser SLAM algorithm and interframe matching optimization method are proposed in this paper. The Bio-RRT independent exploration method is finally proposed, which takes shorter time in equally open space and the search strategy for multiintersection space is more efficient. The experimental results demonstrate that the proposed upgrade SLAM and Bio-RRT methods can better complete the underground space exploration task.

Details

Robotic Intelligence and Automation, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2754-6969

Keywords

Article
Publication date: 4 May 2021

Luitpold Babel

A major challenge for mission planning of aircraft is to generate flight paths in highly dynamic environments. This paper presents a new approach for online flight path planning…

Abstract

Purpose

A major challenge for mission planning of aircraft is to generate flight paths in highly dynamic environments. This paper presents a new approach for online flight path planning with flight time constraints for fixed-wing UAVs. The flight paths must take into account the kinematic restrictions of the vehicle and be collision-free with terrain, obstacles and no-fly areas. Moreover, the flight paths are subject to time constraints such as predetermined time of arrival at the target or arrival within a specified time interval.

Design/methodology/approach

The proposed flight path planning algorithm is an evolution of the well-known RRT* algorithm. It uses three-dimensional Dubins paths to reflect the flight capabilities of the air vehicle. Requirements for the flight time are realized by skillfully concatenating two rapidly exploring random trees rooted in the start and target point, respectively.

Findings

The approach allows to consider static obstacles, obstacles which might pop up unexpectedly, as well as moving obstacles. Targets might be static or moving with constantly changing course. Even a change of the target during flight, a change of the target approach direction or a change of the requested time of arrival is included.

Originality/value

The capability of the flight path algorithm is demonstrated by simulation results. Response times of fractions of a second qualify the algorithm for real-time applications in highly dynamic scenarios.

Details

International Journal of Intelligent Unmanned Systems, vol. 10 no. 4
Type: Research Article
ISSN: 2049-6427

Keywords

Article
Publication date: 20 March 2017

Thomas Fridolin Iversen and Lars-Peter Ellekilde

For robot motion planning there exists a large number of different algorithms, each appropriate for a certain domain, and the right choice of planner depends on the specific use…

1200

Abstract

Purpose

For robot motion planning there exists a large number of different algorithms, each appropriate for a certain domain, and the right choice of planner depends on the specific use case. The purpose of this paper is to consider the application of bin picking and benchmark a set of motion planning algorithms to identify which are most suited in the given context.

Design/methodology/approach

The paper presents a selection of motion planning algorithms and defines benchmarks based on three different bin-picking scenarios. The evaluation is done based on a fixed set of tasks, which are planned and executed on a real and a simulated robot.

Findings

The benchmarking shows a clear difference between the planners and generally indicates that algorithms integrating optimization, despite longer planning time, perform better due to a faster execution.

Originality/value

The originality of this work lies in the selected set of planners and the specific choice of application. Most new planners are only compared to existing methods for specific applications chosen to demonstrate the advantages. However, with the specifics of another application, such as bin picking, it is not obvious which planner to choose.

Details

Industrial Robot: An International Journal, vol. 44 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 14 September 2023

Xunlei Shi, Qingyuan Wu, Jianjian Deng, Ken Chen and Jiwen Zhang

The purpose of this paper is to propose a strategy for the final assembly of helicopter fuselage with weak rigidity parts and mismatched jointing butt ends.

Abstract

Purpose

The purpose of this paper is to propose a strategy for the final assembly of helicopter fuselage with weak rigidity parts and mismatched jointing butt ends.

Design/methodology/approach

The strategy is based on path planning methods. Compared with traditional path planning methods, the configuration-space and collision detection in the method are different. The obstacles in the configuration-space are weakly rigid and allow continuous contact with the robot. The collision detection is based on interference magnitudes, and the result is divided into no collision, weak collision and strong collision. Only strong collision is unacceptable. Then a compliant jointing path planning algorithm based on RRT is designed, combined with some improvements in search efficiency.

Findings

A series of planning results show that the efficiency of this method is higher than original RRT under the same conditions. The effectiveness of the method is verified by a series of simulations and experiments on two sets of systems.

Originality/value

There are few reports on the automation technology of helicopter fuselage assembly. This paper analyzes the problem and provides a solution from the perspective of path planning. This method contains a new configuration-space and collision detection method adapted to this problem and could be intuitive for the jointing of other weakly rigid parts.

Details

Robotic Intelligence and Automation, vol. 43 no. 5
Type: Research Article
ISSN: 2754-6969

Keywords

Article
Publication date: 1 March 1991

Chris Gardiner and John Henneberry

Develops a habit‐persistence model which is based on the assumptionthat experience conditions present behaviour and expectations. Notesthat the model combines the adaptive…

Abstract

Develops a habit‐persistence model which is based on the assumption that experience conditions present behaviour and expectations. Notes that the model combines the adaptive expectations hypothesis with the partial adjustment process. Concludes that accurate forecasts for declining regions are produced but the results for growing regions are not significant.

Details

Journal of Property Valuation and Investment, vol. 9 no. 3
Type: Research Article
ISSN: 0960-2712

Keywords

Article
Publication date: 27 September 2011

Colm McKeown and Phil Webb

The purpose of this paper is to describe the development, testing and scientific evaluation of a novel, load‐cell‐controlled reactive reconfigurable tooling (RRT) solution. This…

1000

Abstract

Purpose

The purpose of this paper is to describe the development, testing and scientific evaluation of a novel, load‐cell‐controlled reactive reconfigurable tooling (RRT) solution. This RRT not only addresses the underlying inherent problems with traditional reconfigurable tools but also potentially expands their use into the area of condition monitoring.

Design/methodology/approach

The paper covers the design intent and methodology. The construction and evaluation of both a simple prototype and a fully functional tool are described.

Findings

The tool was successfully demonstrated using friction stir welding (FSW) of fuselage panels as a demanding application and the full functionality of the tool was demonstrated. The condition and process monitoring system was also demonstrated and shown to be able to distinguish both between different types of weld and tool failure conditions.

Research limitations/implications

Having successfully designed and tested the novel RRT system under the extreme conditions of FSW, it is apparent that there are many more applications and developments that this system could be used for. The same requirements for accurate control of geometry exist in processes such as water jet cutting, trimming and machining. However, there was not sufficient resource or time within the research programme to verify this. One disadvantage of the tool is the cost of the individual load cells and the associated charge amplifiers; however, this cost is offset by the opportunity to use them in a tool condition monitoring function as well.

Practical implications

The tool developed not only has the potential to provide cost benefits but also time reductions due to the elimination of the need to move large and heavy tools in and out of the FSW machine when part production runs are changed.

Originality/value

The originality of work described is the tool's ability to both adapt and monitor the component being held. This places it considerably beyond the state of the art in large‐scale industrial reconfigurable tooling. The research's value lies in applicability and demonstration for real production parts and processes.

Details

Assembly Automation, vol. 31 no. 4
Type: Research Article
ISSN: 0144-5154

Keywords

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