Yaxiong Wu, Jiahao Chen and Hong Qiao
The purpose of this study is realizing human-like motions and performance through musculoskeletal robots and brain-inspired controllers. Human-inspired robotic systems, owing to…
Abstract
Purpose
The purpose of this study is realizing human-like motions and performance through musculoskeletal robots and brain-inspired controllers. Human-inspired robotic systems, owing to their potential advantages in terms of flexibility, robustness and generality, have been widely recognized as a promising direction of next-generation robots.
Design/methodology/approach
In this paper, a deep forward neural network (DFNN) controller was proposed inspired by the neural mechanisms of equilibrium-point hypothesis (EPH) and musculoskeletal dynamics.
Findings
First, the neural mechanism of EPH in human was analyzed, providing the basis for the control scheme of the proposed method. Second, the effectiveness of proposed method was verified by demonstrating that equilibrium states can be reached under the constant activation signals. Finally, the performance was quantified according to the experimental results.
Originality/value
Based on the neural mechanism of EPH, a DFNN was crafted to simulate the process of activation signal generation in human motion control. Subsequently, a bio-inspired musculoskeletal robotic system was designed, and the high-precision target-reaching tasks were realized in human manner. The proposed methods provide a direction to realize the human-like motion in musculoskeletal robots.
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Shanlin Zhong, Ziyu Chen and Junjie Zhou
Human-like musculoskeletal robots can fulfill flexible movement and manipulation with the help of multi joints and actuators. However, in general, sophisticated structures…
Abstract
Purpose
Human-like musculoskeletal robots can fulfill flexible movement and manipulation with the help of multi joints and actuators. However, in general, sophisticated structures, accurate sensors and well-designed control are all necessary for a musculoskeletal robot to achieve high-precision movement. How to realize the reliable and accurate movement of the robot under the condition of limited sensing and control accuracy is still a bottleneck problem. This paper aims to improve the movement performance of musculoskeletal system by bio-inspired method.
Design/methodology/approach
Inspired by two kinds of natural constraints, the convergent force field found in neuroscience and attractive region in the environment found in information science, the authors proposed a structure transforming optimization algorithm for constructing constraint force field in musculoskeletal robots. Due to the characteristics of rigid-flexible coupling and variable structures, a constraint force field can be constructed in the task space of the musculoskeletal robot by optimizing the arrangement of muscles.
Findings
With the help of the constraint force field, the robot can complete precise and robust movement with constant control signals, which brings in the possibility to reduce the requirement of sensing feedback during the motion control of the robot. Experiments are conducted on a musculoskeletal model to evaluate the performance of the proposed method in movement accuracy, noise robustness and structure sensitivity.
Originality/value
A novel concept, constraint force field, is proposed to realize high-precision movements of musculoskeletal robots. It provides a new theoretical basis for improving the performance of robotic manipulation such as assembly and grasping under the condition that the accuracy of control and sensory are limited.
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Qiao Qiao, Jianping Yuan and Xin Ning
The purpose of this paper is to establish the dynamics model of a Z-folded PhoneSat considering hinge friction and to investigate the influence of disturbances, such as friction…
Abstract
Purpose
The purpose of this paper is to establish the dynamics model of a Z-folded PhoneSat considering hinge friction and to investigate the influence of disturbances, such as friction, stiffness asymmetry, deployment asynchronicity and initial disturbance angular velocity, on the attitude of PhoneSat during and after deployment.
Design/methodology/approach
For the Z-folded PhoneSat, the dynamics model considering hinge friction is established and the dynamics simulation is carried out. The effects of friction, stiffness asymmetry, deployment asynchronicity and initial disturbance angular velocity on the attitude motion of the PhoneSat are studied and the attitude motion regularities of the PhoneSat considering the disturbance factors mentioned above are discussed.
Findings
Friction has a main contribution to reducing the oscillation of attitude motion and damping out the residual oscillation, ultimately decreasing the deployment time. An increasing length of deployment time is required with the increasing stiffness asymmetry and time difference of asynchronous deployment, which also have slight disturbances on the attitude angle and angular velocity of PhoneSat after the deployment. The initial disturbance angular velocity in the direction of deployment would be proportionally weakened after the deployment, whereas initial disturbance angular velocity in other direction induces angular velocities of other axes, which dramatically enhances the complexity of attitude control.
Originality/value
The paper is a useful reference for engineering design of small satellites attitude control system.
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Tooraj Karimi and Yalda Yahyazade
Risk management is one of the most influential parts of project management that has a major impact on the success or failure of projects. Due to the increasing use of information…
Abstract
Purpose
Risk management is one of the most influential parts of project management that has a major impact on the success or failure of projects. Due to the increasing use of information technology in all fields and the high failure rate of software development projects, it is essential to predict the risk level of each project effectively before starting. Therefore, the main purpose of this paper is proposing an expert system to infer about the risk of new banking software development project.
Design/methodology/approach
In this research, the risk of software developing projects is considered from four dimensions including risk of cost deviation, time deviation, quality deviation and scope deviation, which is examined by rough set theory (RST). The most important variables affecting the cost, time, quality and scope of projects are identified as condition attributes and four initial decision systems are constructed. Grey system theory is used to cluster the condition attributes and after data discretizing, eight rule models for each dimension of risk as a decision attribute are extracted using RST. The most validated model for each decision attribute is selected as an inference engine of the expert system, and finally a simple user interface is designed in order to predict the risk level of any new project by inserting the data of project attributes
Findings
In this paper, a high accuracy expert system is designed based on the combination of the grey clustering method and rough set modeling to predict the risks of each project before starting. Cross-validation of different rule models shows that the best model for determining cost deviation is Manual/Jonson/ORR model, and the most validated models for predicting the risk of time, quality and scope of projects are Entropy/Genetic/ORR, Manual/Genetic/FOR and Entropy/Genetic/ORR models; all of which are more than 90% accurate
Research limitations/implications
It is essential to gather data of previous cases to design a validated expert system. Since data documentation in the field of software development projects is not complete enough, grey set theory (GST) and RST are combined to improve the validity of the rule model. The proposed expert system can be used for risk assessment of new banking software projects
Originality/value
The risk assessment of software developing projects based on RST is a new approach in the field of risk management. Furthermore, using the grey clustering for combining the condition attributes is a novel solution for improving the accuracy of the rule models.
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C.Y. Yang, J. Qiao, E.M. Ajimine and P.P. Patel
The objectives of this study are to assess the utility of the high‐Tc superconductor, yttrium barium copper oxide (YBCO), as a gate material in two‐ and three‐terminal…
Abstract
The objectives of this study are to assess the utility of the high‐Tc superconductor, yttrium barium copper oxide (YBCO), as a gate material in two‐ and three‐terminal superconductor‐insulator‐semiconductor (SulS) devices, and to study the electrical properties of the insulator and the insulator/Si interface. The YBCO and yttria‐stabilised‐zirconia (YSZ) layers were epitaxially grown on Si by pulsed‐laser deposition. The SulS diodes were fabricated using standard lithographic techniques, with evaporated gold providing the gate and substrate contacts. Electrical characterisation of these superconducting devices is performed using current vs. voltage and capacitance vs. voltage (C‐V) measurements under bias‐temperature cycling. It is found that deposition of thicker YBCO films (≥ 1500 A) minimises the leakage current of the devices, resulting in electrically stable capacitors, especially at superconducting temperatures. A thermally activated process in the temperature range 80–295 K, as determined from flat‐band shifts of C‐V curves, is attributed to trapping/detrapping mechanisms in the SiOx interfacial layer between YSZ and Si. The mobile ions present in YSZ, which affect the room‐temperature C‐V behaviour, give rise to adjustable threshold voltages at superconducting temperatures. These findings will have a significant impact on future transistors using this capacitor as the gate structure.
Dynamic movement primitives (DMPs) is a general robotic skill learning from demonstration method, but it is usually used for single robotic manipulation. For cloud-based robotic…
Abstract
Purpose
Dynamic movement primitives (DMPs) is a general robotic skill learning from demonstration method, but it is usually used for single robotic manipulation. For cloud-based robotic skill learning, the authors consider trajectories/skills changed by the environment, rebuild the DMPs model and propose a new DMPs-based skill learning framework removing the influence of the changing environment.
Design/methodology/approach
The authors proposed methods for two obstacle avoidance scenes: point obstacle and non-point obstacle. For the case with point obstacles, an accelerating term is added to the original DMPs function. The unknown parameters in this term are estimated by interactive identification and fitting step of the forcing function. Then a pure skill despising the influence of obstacles is achieved. Using identified parameters, the skill can be applied to new tasks with obstacles. For the non-point obstacle case, a space matching method is proposed by building a matching function from the universal space without obstacle to the space condensed by obstacles. Then the original trajectory will change along with transformation of the space to get a general trajectory for the new environment.
Findings
The proposed two methods are certified by two experiments, one of which is taken based on Omni joystick to record operator’s manipulation motions. Results show that the learned skills allow robots to execute tasks such as autonomous assembling in a new environment.
Originality/value
This is a new innovation for DMPs-based cloud robotic skill learning from multi-scene tasks and generalizing new skills following the changes of the environment.
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Gan Zhan, Zhenyu Zhang, Zhihua Chen, Tianzhen Li, Dong Wang, Jigang Zhan and Zhengang Yan
This paper aims to focus on the spatial docking task of unmanned vehicles under ground conditions. The docking task of military unmanned vehicle application scenarios has strict…
Abstract
Purpose
This paper aims to focus on the spatial docking task of unmanned vehicles under ground conditions. The docking task of military unmanned vehicle application scenarios has strict requirements. Therefore, how to design a docking robot mechanism to achieve accurate docking between vehicles has become a challenge.
Design/methodology/approach
In this paper, first, the docking mechanism system is described, and the inverse kinematics model of the docking robot based on Stewart is established. Second, the genetic algorithm-based optimization method for multiobjective parameters of parallel mechanisms including workspace volume and mechanism flexibility is proposed to solve the problem of multiparameter optimization of parallel mechanism and realize the docking of unmanned vehicle space flexibility. The optimization results verify that the structural parameters meet the design requirements. Besides, the static and dynamic finite element analysis are carried out to verify the structural strength and dynamic performance of the docking robot according to the stiffness, strength, dead load and dynamic performance of the docking robot. Finally, taking the docking robot as the experimental platform, experiments are carried out under different working conditions, and the experimental results verify that the docking robot can achieve accurate docking tasks.
Findings
Experiments on the docking robot that the proposed design and optimization method has a good effect on structural strength and control accuracy. The experimental results verify that the docking robot mechanism can achieve accurate docking tasks, which is expected to provide technical guidance and reference for unmanned vehicles docking technology.
Originality/value
This research can provide technical guidance and reference for spatial docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.
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Tooraj Karimi and Jeffrey Yi-Lin Forrest
The purpose of this paper is to analyze the energy audit reports in order to define the most favorable factors affecting energy consumption of buildings. Since energy audit of…
Abstract
Purpose
The purpose of this paper is to analyze the energy audit reports in order to define the most favorable factors affecting energy consumption of buildings. Since energy audit of buildings includes assessment of occupants comfort level in addition to the technical data of buildings so some rules are extracted to model the employees thermal comfort level in organization.
Design/methodology/approach
Some tools of RST and GIA are used in this research to analyze the energy consumption of official buildings. “Average energy consumption of building per year” is selected as a system characteristic in GIA and as a decision attribute in RST to show the behavior of buildings energy consumption. Ten technical sequences of buildings are chosen as relevant factors of behavior and conditional attributes in GIA and RST. In order to model the employees thermal comfort level in organization by RST, ten technical attributes of buildings are selected as condition attributes and thermal comfort level of employees is selected as decision attribute. Due to the different algorithms of data complement, discretization, reduction, and rule generation, four rule models are constructed. Cross-validation is used for evaluation of the model results and the best model is chosen with 62 rules and 99.8 percent of accuracy.
Findings
According to the results of GIA and RST, “Uncontrolled area of the building” has been diagnosed as the most important factor between other relevant factors/attributes and it has the greatest effect on energy consumption of building. Four rule models have been extracted from deferent decision tables in order to describe the thermal comfort level of employees in organization. The maximum number of rules relates to the conditional combination/GA model with 1263 rules and average accuracy of 99.7 percent and the minimum number relates to the conditional combination/Janson model with 62 rules and average accuracy of 99.8 percent.
Research limitations/implications
The total observations for rule extraction is 81 and the results can be improved by further samples.
Originality/value
It shows that “Uncontrolled area of the building” is the most important factor/attribute to define the consumption of buildings and thermal comfort level of employees in organization.
Details
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Yang Liu, Ziyu Chen, Jie Gao, Shuai Gan and Erlong Kang
Compared with the robotic manipulation in structured environment, high performance assembly of complex parts in extreme special environment is facing great challenges because of…
Abstract
Purpose
Compared with the robotic manipulation in structured environment, high performance assembly of complex parts in extreme special environment is facing great challenges because of the uncertainty in the environment, and the decline of the control accuracy of the robot and the sensor accuracy. The assembly and construction of the space station is a typical case. An important step in the construction of the space station is the module positioning and docking with the auxiliary of the space manipulator. The operation of the manipulator is faced with many problems, such as low sensing information accuracy, large end position deviation and the requirement of weak impact in the docking process. The purpose of this paper is to design a docking method at the strategy level to effectively solve the problems that may be faced in the docking process.
Design/methodology/approach
Inspired by the research of robotic high-precision compliant assembly, this paper introduces the concept of Attractive Region in Environment (ARIE) into the space manipulator–assisted module docking. The contact configuration space of the docking mechanism and the existence of ARIE are systematically analyzed. The docking strategy based on ARIE framework is proposed, in which the impedance control is used to ensure the weak impact during the docking process.
Findings
For the androgynous peripheral spacecraft docking mechanism, a large range of attractive region exists in the high-dimensional contact configuration space. The docking strategy based on ARIE framework can be designed according to the geometric characteristics of the constraint region and the structural characteristics of the docking mechanism. The virtual models and the simulation environment are established, and the effectiveness of the proposed method is preliminarily verified.
Originality/value
Based on the research results of robotic precision compliant manipulation, in this paper, the theory of ARIE is first systematically applied to the analysis of spacecraft docking problem and the design of docking scheme. The effectiveness of the proposed docking method is preliminarily verified for the requirements of large position tolerance and weak impact. The research results will provide theoretical support and technical reference for the assembly and construction of space station and other space manipulator operations.
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Ramnath Dixit and Vinita Sinha
This chapter discusses key training challenges that organizations need to confront with the objective of building a robust human resource management system. Given the dynamics of…
Abstract
This chapter discusses key training challenges that organizations need to confront with the objective of building a robust human resource management system. Given the dynamics of the current business environment, training and development has become an indispensable function in global organizations. Building an effective human capital that contributes to continual organizational growth has become the established norm to survive in a competitive business landscape. However, the training and development function is often rendered ineffective, on account of various bottlenecks existing in the organization. Addressing these bottlenecks is quintessential in ensuring the creation of a performance-driven human capital. The goal of this chapter is to draw attention to the training impediments that hinder organizational growth and to diagnose the underlying causes for the same. This chapter concludes with recommendations that organizational decision-makers can leverage in their quest to strengthen the human capital, by utilizing their training and development infrastructure optimally.