Contact State Transitions Research Articles

Study on wear characteristics and authorized limits of switch rails of high-speed turnout

PurposeIt is quite universal for high-speed turnouts to be exposed to the wear of the stock rail of the switch rail during the service process. The wear will cause the change of railhead profile and the relative positions of the switch rail and the stock rail, which will directly affect the wheel–rail contact state and wheel load transition when a train passes the turnout and will further impose serious impacts on the safety and stability of train operation. The purpose of this paper is to provide suggestions for wear management of high-speed turnout.Design/methodology/approachThe actual wear characteristics of switch rails of high-speed turnouts in different guiding directions were studied based on the monitoring results on site; the authorized wear limits for the switch rails of high-speed turnout were studied through derailment risk analysis and switch rail strength analysis.FindingsThe results show that: the major factor for the service life of a curved switch rail is the lateral wear. The wear characteristics of the curved switch rail of a facing turnout are significantly different from those of a trailing turnout. To be specific, the lateral wear of the curved switch rail mainly occurs in the narrower section at its front end for a trailing turnout, but in the wider section at its rear end when for a facing turnout. The maximum lateral wear of a dismounted switch rail from a trailing turnout is found on the 15-mm wide section and is 3.9 mm, which does not reach the specified limit of 6 mm. For comparison, the lateral wear of a dismounted switch rail from a facing turnout is found from the 35-mm wide section to the full-width section and is greater than 7.5 mm, which exceeds the specified limit. Based on this, in addition to meeting the requirements of maintenance rules, the allowed wear of switch rails of high-speed turnout shall be so that the dangerous area with a tangent angle of wheel profile smaller than 43.6° will not contact the switch rail when the wheel is lifted by 2 mm. Accordingly, the lateral wear limit at the 5-mm wide section of the curved switch rail shall be reduced from 6 mm (as specified) to 3.5 mm.Originality/valueThe work in this paper is of reference significance to the research on the development law of rail wear in high-speed turnout area and the formulation of relevant standards.

Peg-in-Hole Using Transient Information of Force Response

In precision assembly, a peg is guided into a hole with a tolerance smaller than the position accuracy. Although force/torque sensing can estimate the relative position between the peg and hole accurately, its performance is impaired because of the degradation of estimation accuracy caused by transient error at the time of the collision. We found in this study that if contact state transitions can be generated reproducibly, accurate relative positions can be derived from the transient responses, which were previously regarded as errors. We propose a method that focuses on this characteristic. The transition in the contact state is determined by force/torque responses. Then, the estimation accuracy of the direction of the hole improves by using only the force/torque responses of a specific contact state. Additionally, the time between the contact and estimation of the relative position is reduced by using the transient force information.

A Novel Contact State Estimation Method for Robot Manipulation Skill Learning via Environment Dynamics and Constraints Modeling

Nowadays the robot manipulation skills are usually learned by human demonstration via trajectory-level learning, which somewhat lacks robustness and generalization. In this paper, we propose a novel contact state level learning method for robot manipulation skill acquisition via human demonstration. The robot-environment contact states are described via environment dynamics modelling and geometric constraints modelling for flexible contact and rigid contact cases, respectively. During human demonstration process, the robot-environment interaction force, the robot position, and velocity data are collected. After that, the environment dynamics and geometric constraints modelling methods are presented to determine the contact state changes during the robot manipulation process. Then the robot manipulator learns the contact state information rather than specific manipulation trajectory. On this basis, the manipulation control law using active exploration method is presented to control the robot during the button pressing process and peg-hole-insertion process, respectively. Finally, the performance of the presented methodology has been verified via experimental studies. Note to Practitioners—Intelligent robots will become the right assistants of human beings in the future, especially in various areas of manipulation occasions. The important premise of realizing this vision is that the robots should have certain ability of manipulation skill learning. A lot of research has been carried out in this field, many of which are focusing on trajectory level manipulation skill learning and reproduction. Other than the trajectory level learning, human beings can learn many other higher levels of manipulation skills, such as the contact state level and semantic level learning, which makes the learning results more robust and general. In this paper, the contact state estimation and learning method via environment dynamics and geometric constraints modelling is presented to learn the robot manipulation skill based on the contact state transition conditions. In this way, the robot needs less data in the skill learning process, and the trajectory level learning is avoided. After learning the contact state level manipulation skill, the lower trajectory level command is autonomously generated. Experiments on button pressing and peg-hole-insertion tasks by KUKA iiwa robot have obtained very good results. Other than the button pressing and peg-hole-insertion tasks, the presented methodology can be applied to many other manipulation tasks, as long as there are contact state changes in the manipulation process. The work of this paper lays a foundation for the robot learning of higher-level manipulation skills.

Realization of Multi Contact Behaviors Using Contact-State Transition Model and Reinforcement Learning by Musculoskeletal Humanoid

Realization of Multi Contact Behaviors Using Contact-State Transition Model and Reinforcement Learning by Musculoskeletal Humanoid

Subsonic to Intersonic Transition in Sliding Friction for Soft Solids.

We perform friction experiments between a compliant gel and a rigid cylinder at sliding velocities comparable to the Rayleigh wave or secondary wave velocity of the gel. We find that, when the sliding velocity exceeds the wave velocities, the contact state transitions from Hertzian like to flat punch like, resulting in the breakdown of the lubricating oil film and the abrupt increase in the friction coefficient. We succeed in deriving theoretical solutions for the contact pressure distributions and the deformation profiles in the presence of friction, which are consistent with our experimental observations.

Electrically modulated adhesive hydrophobicity for patterning various microstructures

In this study, we present an approach for patterning various microstructures using modulated electric-field. Experimentally, electrical potential was applied to the water droplet on the micropillar or microhole array textured dielectric surfaces, contact state transition could occur from Cassie-Baxter mode to Wenzel mode, and therefore enhance the adhesive hydrophobic property. The liquid droplet would spread over the microstructure dielectric surface and fill up the asperities around the micropillar or microhole array structures, which was indicated clearly by UV-curable polymer deformation under electric-field and solidification under UV irradiation. By this means, microstructures of UV-curable polymer with various morphologies including microlens, microbump and micropillar array structures could be generated by tuning the applied voltage.

A smooth contact-state transition in a dynamic model of rolling-element bearings

We present a new formulation to calculate the response of a system containing rolling-element bearings operating under a radial clearance and a dominant radial load. The nonlinear bearing force- and stiffness-displacement characteristics in combination with the bearing clearance necessitate an advanced numerical analysis. The response of a shaft-bearing-housing assembly can be unstable in the transient regions, e.g., at the start of a system run-up or when passing the critical speed of a system. This can lead to long computational times or even to non-converged solutions. In this paper, a new analytical bearing-stiffness model is presented that is capable of overcoming these problems by smoothing the nonlinear bearing force- and stiffness-displacement characteristics in the discontinuous regions. The smoothing is implemented on the deformation scale. The proposed model is modular, allowing us to define a specific value of the smoothing to each rolling element that comes into contact. A simple case study that involves two bearings of different types (ball and cylindrical roller) is presented. They support an unbalanced rotor, subjected to a constant angular acceleration. We show that a small smoothing value can significantly enhance the numerical calculation of the chosen system in terms of speed and stability.

Recognition of in-hand manipulation using contact state transition for multifingered robot hand control

This paper proposes a method for recognizing in-hand manipulation of the operator by observing a contact state transition between an object and the human hand. An instrumented object with a pressure distribution sensor and a position/orientation sensor has been developed. By processing information from the sensors, the contact regions on the operator’s palm surface are detected. A contact state transition diagram is created by taking practical contact states into account. A recognition algorithm based on Dynamic Programming (DP) is proposed to recognize the type of in-hand manipulation by comparing the similarity of the contact state transition between an input sequence and template manipulation primitives. The validity of the proposed method is confirmed by experiments.

掌面の接触状態遷移を用いた円柱物体の操作認識

掌面の接触状態遷移を用いた円柱物体の操作認識

Evaluation of Manipulative Familiarization and Fatigue Using Contact State Transition on Palm Surface

In this research, we propose a method for generating a template used for the recognition of manipulation in consideration of the familiarization and the fatigue. We made a system that can evaluate a quantitative comparison of the similarity among manipulations performed by observing the contact state transition on the palm surface. This system can detect the contact state on the palm surface by attaching a tactile sensor sheet on the manipulated object. In the experiment, the familiarization and the fatigue are detected by measuring the variance of manipulation. The experimental result indicates that manipulation is able to be divided into three terms, which are the proficiency process, the familiarization and the fatigue. It is also indicated that the variation of the manipulation becomes small when the template is generated by the manipulation data in the familiarization term.

1P1-S-032 掌面の接触状態遷移と操作物体形状の関連性解析(作業をするロボット2,生活を支援するロボメカ技術のメガインテグレーション)

1P1-S-032 掌面の接触状態遷移と操作物体形状の関連性解析(作業をするロボット2,生活を支援するロボメカ技術のメガインテグレーション)

実演教示による多角形ワーク組立のための局所的な接触状態遷移モデル群の生成

Modeling contact-state transitions is very troublesome. To deal with this problem, we have investigated a method of allocating local contact-state transition models (local models) to vertex pairs on which contact-state transitions occur and grouping the allocated local models according to a task process. In this paper, we propose a method of the allocation and the grouping from human demonstrations. Concretely, (i) for the allocation, vertex pairs where contact-state transitions occurred are found by using C-constrains in demonstrated data and (ii) the directions of contact-state transitions or the scope of the allocated local models are investigated for the grouping. We applied our method to some insertion tasks and tested it by performing the tasks by a compliance-controlled robot which had the generated groups of the local models. The experimental results showed the groups of local models work well as models of contact-state transition. As the result, we verified usefulness of our proposed method.

実環境行動計画機能に基づく作業ロボットシステム

This paper describes a teleoperation system for maintenance tasks integrating planning functions based on manipulation skills. Demands for autonomous teleoperation function for maintenance tasks are increasing. We embed planning functions into a telerobotics system to make the system more flexible and robust. A motion teaching system based on contact state transition in a task in VR, a geometric modeling system using Teaching Trees, and a task execution system based on manipulation skills are integrated. The design concept of the system and essential technologies are described. An experimental task is explained to demonstrate the efficiency of the telerobotics system.

実演教示による組立作業モデルの生成

We propose a method for generating an assembly-task model from human demonstration. The model is pairs of operational coordinates and local contact-state transition models (local models) allocated in the coordinates. To generate the model, (1) the demonstrated data is segmented in each contact-state transition, (2) the segmented data is analyzed for setting operational coordinates using the component principal analysis, and (3) the local models are allocated to contact vertex pairs projected onto the operational coordinates. The usefulness of our method is discussed by the analysis results of demonstration in two assembly tasks and the robot task-execution using the generated models.

線形相補性問題に基づく多剛体操り系の接触状態遷移に関する動力学解法

線形相補性問題に基づく多剛体操り系の接触状態遷移に関する動力学解法

Contact-State Transition Graph for Graspless Manipulation Planning.

In this paper, we propose contact-state transition for planning of graspless manipulation. Graspless manipulation is human-like dexterous manipulation method in which robot fingers do not grasp an object and manipulate it with support by environment. In graspless manipulation, the object contacts with environment several ways. Several patterns of contact state between an object and environment are described as nodes of graph and are connected by arcs which describe grapsless manipulation methods. From this graph, we can find the minimum cost path from start state to goal state. For correct a cost and state transition, we introduce parameterized node in the graph.

直方体のハンドリングにおける制御レベルの基本動作解析

Manipulation system for rectangular shaped object based on primitive motions is presented. Tasks involving contact with the environment require adjustment of control parameters for specific contact state for each application. In order to alleviate this problem, control programs for primitive motions have been implemented in the robot controller. This is based on an assumption that most tasks can be decomposed into a finite set of primitive motions, and that a task can be fulfilled by executing a sequence of primitive motions. In this paper, the object's shape is restricted to prism. The environment was also assumed to be composed of vertices, edges, and planes. First, all possible contact states were analyzed, and a control program for each contact state was written based on impedance control. Signal processing of the force sensor is presented. An experiment where a wooden block grabbed by a robot hand passed through a maze-like environment is presented. The system detected the contact state transition and chosed the appropriate primitive motion as it moved.

複数の局所的な接触状態遷移モデルに基づく組立動作計画

複数の局所的な接触状態遷移モデルに基づく組立動作計画

Dynamically Reconfigurable Robotic System. 24th Report. Skill Learning of Dual-Peg-in-Hole Using Hidden Markov Model.

A skill learning method is proposed in this paper. For a Dual-peg-in-hole problem, it is very difficult to analyze force and contact status. To extract the human skill of this kind of work, we record the force/torque data, sequence data, and psychological data by observing human work. Since human performance is inherently stochastic, we use a Hidden Markov Model (HMM) to represent these characteristics. By trainning the HMM using human data, we obtain a reasonable sequence of Dual-peg-in-hole work and the threshold of contact-state transition. We represent the human skill as a set of simple production rules that can easily be adopted into an actual manipulator system. This method is used in the assembly of self-organizing manipulator cells. The simulations and experiments illustrate the effectiveness of the algorithm.

The Discrete Event Modeling and Trajectory Planning of Robotic Assembly Tasks

A new approach to process modeling, task synthesis, and trajectory planning for robotic assembly is presented. Assembly is modeled as a discrete event dynamic system incorporating both discrete and continuous aspects of the process. The discrete event nature of assembly due to contact state transitions is modeled using Petri nets. The Petri net modeling enables a compact graphical description of causal contact state transitions and provides a coherent mathematical representation of both the discrete and continuous dynamics. In contrast to the traditional contact state network, the Petri net modeling also incorporates causality. Using discrete event modeling, an efficient assembly strategy is found. A discrete event trajectory is determined using dynamic programming to minimize the path length and the uncertainty during assembly. Lastly, an optimal event trajectory is calculated to demonstrate the method. This paper lays the foundation of discrete event modeling for robotic assembly. An new avenue for the analysis and synthesis of significant aspects of the assembly process is opened.