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1 – 10 of over 42000Yi Liu, Meng Joo Er and Chen Guo
The purpose of this paper is to propose an efficient path and trajectory planning method to solve online robotic multipoint assembly.
Abstract
Purpose
The purpose of this paper is to propose an efficient path and trajectory planning method to solve online robotic multipoint assembly.
Design/methodology/approach
A path planning algorithm called policy memorized adaptive dynamic programming (PM-ADP) combines with a trajectory planning algorithm called adaptive elite genetic algorithm (AEGA) for online time-optimal path and trajectory planning.
Findings
Experimental results and comparative study show that the PM-ADP is more efficient and accurate than traditional algorithms in a smaller assembly task. Under the shortest assembly path, AEGA is used to plan the time-optimal trajectories of the robot and be more efficient than GA.
Practical implications
The proposed method builds a new online and efficient path planning arithmetic to cope with the uncertain and dynamic nature of the multipoint assembly path in the Cartesian space. Moreover, the optimized trajectories of the joints can make the movement of the robot continuously and efficiently.
Originality/value
The proposed method is a combination of time-optimal path planning with trajectory planning. The traveling salesman problem model of assembly path is established to transfer the assembly process into a Markov decision process (MDP). A new dynamic programming (DP) algorithm, termed PM-ADP, which combines the memorized policy and adaptivity, is developed to optimize the shortest assembly path. GA is improved, termed AEGA, which is used for online time-optimal trajectory planning in joints space.
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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 and the…
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.
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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 limit energy…
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.
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Alireza Pooya, Morteza Pakdaman and Shila Monazam Ebrahimpour
This paper aims to present a continuous-time workforce planning model in which workforce flow occurs in terms of internal and external recruitment considering human resource…
Abstract
Purpose
This paper aims to present a continuous-time workforce planning model in which workforce flow occurs in terms of internal and external recruitment considering human resource strategies (HRS). The proposed model is a linear optimal control model in which promotions occur by inside appointment and outside employment of the system considering a cost leadership or a differentiation strategy and whether organizations have an internal or an external recruitment orientation. In other words, in the model and its solution procedure, this paper could determine any arbitrary function for the demand of the workforce with each HRS.
Design/methodology/approach
The proposed model contains five main sections, namely, applicants, newcomers, workforce who are doing sensitive-simple jobs, expert workforce and supervisors (or managers) that have a different orientation in different HRS. Each of these sections has a target value that this paper tries to attain it by applying appropriate control variables, such as recruitment, layoff, degradation, promotion and retirement. To reach this purpose, this paper formulated an optimal control problem using a linear system transition equation with a quadratic cost function.
Findings
Based on the proposed model, it was found that the optimal control model can interpret the managerial aspects. This model could be useful for different firms with different types of workforce demands. This paper has tried to have a comprehensive view of different flows of the workforce in an organization that concern to workforce planning.
Originality/value
Despite the considerable amount of research published, and the importance of following a human resources strategy from organizational strategy, in the knowledge, there is no comprehensive study dedicated to human resources strategy and workforce planning by optimal control models for workforce planning.
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Ignacio J. RAMIREZ‐ROSADO and R.N. ADAMS
Multiobjective planning models for electric power distribution system planning can include multiple aspects such as community amenity values, geographical conditions of the study…
Abstract
Multiobjective planning models for electric power distribution system planning can include multiple aspects such as community amenity values, geographical conditions of the study area, reliability evaluations (mainly in terms of service continuity), or the optimal voltage profile in the network, as well as the basic planning aspects: power demand requirements, power capacity limits and the minimization of the total system expansion costs. On the other hand, classical single objective planning models have usually considered only the basic aspects. This paper describes a multiobjective model to find the optimal voltage profile and to look for the least cost system expansion simultaneously. Furthermore, two multiobjective techniques for the application of the model to distribution system expansion problems are outlined. The computer results have shown that multiobjective models are able to find solutions which include multiple planning objectives simultaneously, and that these solutions are advantageous compared with the ones from classical single objective models.
Develops a linear programming model for integrated production planning based on the practice of a major Canadian steel making company. Considers the entire planning activity in…
Abstract
Develops a linear programming model for integrated production planning based on the practice of a major Canadian steel making company. Considers the entire planning activity in the company as an integrated process involving a number of closely related sub‐functions, such as raw material purchasing, semi‐finished product purchasing and production, and capacity allocation, as well as finished product production and distribution. The mathematical programming model takes into account production costs, product throughput rates, customer demands, sales prices and facility capacities for optimal production planning. Presents a numerical example based on realistic system structure and practical planning data to illustrate the model. Computation results and analysis show that the integrated methodology is a feasible and practical approach for steel production planning.
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Sanjay Choudhari and Amit Tindwani
This study aims to assist the project manager in minimising the material logistics cost of road project by planning the optimal movement of aggregate across three stages of supply…
Abstract
Purpose
This study aims to assist the project manager in minimising the material logistics cost of road project by planning the optimal movement of aggregate across three stages of supply chain: sourcing, processing and distribution.
Design/methodology/approach
The paper conceptualises the raw material consumption in a road project as a logistics network distribution problem. A linear programming (LP) formulation is constructed with appropriate decision variables by integrating the three stages of material movement. The series of LP scenarios are solved using an LP solver to decide the optimal movement of the aggregate to be consumed in different layers of road segments.
Findings
The results obtained from the model show that planning material logistics of an entire road project using optimisation provides substantial saving in logistics costs than using common sense. Further, the magnitude of cost saving improves as the complexity of the model increases in term of enormous feasible options.
Practical implications
The model shown in this paper may serve as a basis for planning the logistics of raw materials consumed in the road projects. The small improvement in material flows by optimising supply chain shows sensible cost benefit to the project manager and hence control and monitor the overall cost and activities of the project. The output of the model is also expected to help the project team as an input in the decision-making processes such as appropriate material sourcing contract, capacity assessment of material processing facility and transportation planning.
Originality/value
While the optimisation models are widely used and popular among the many industrial applications, this research shows distinct application of such a model in managing the logistics of the road construction project.
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