Modelling of Cutting Force and Robot Load during Machining

2014 ◽  
Vol 1036 ◽  
pp. 715-720 ◽  
Author(s):  
Grzegorz Gołda ◽  
Adrian Kampa
Keyword(s):  
Cutting Force ◽  
Dimensional Space ◽  
Mechanistic Model ◽  
Soft Materials ◽  
Industrial Robots ◽  
Robot Arm ◽  
Skilled Workers ◽  
Robot Machining ◽  
Sharp Edges ◽  
Robot Selection

Industrial robots are used for many tasks, mainly for material handling, welding and cutting. Robots can be also equipped with other tools for example drill or mill cutter and used for machining. Compared to conventional machines, robots have some advantages, which are: large range, flexibility and speed. On the other hand the greater disadvantage is small stiffness of robotic arms. Also the precision of robot positioning is smaller than modern CNC machines. Nowadays small number of robots are used mainly for machining of soft materials, such as plastic, wood, foam and aluminium. We have also executed some experiments with robot machining including styrodur milling. This technique is similar to rapid prototyping technics. Obtained parts can be used as prototypes. Robots can be used also for machining of hard materials and steel, but that is related with greater cutting force. Thanks they flexibility robots can be used for tasks that are performed by hand by locksmiths. An example of deburring and chamfering of sharp edges were analysed. The burrs and sharp edges that remains after some machining operations must be removed. In most cases that is done by chamfering the edges with hand tools. That tasks requires skilled workers and is physically exhausting and therefore industrial robots can be used to perform that work. But the first problem is prediction of cutting force and selection of proper robot with adequate payload. A mechanistic model of cutting force during milling a chamfer on the edge is presented in the article. Obtained results are similar with other experimental results that are described in the analysed bibliography. Afterwards a methodology for robot selection is explained. Because robot manufacturers give only data for static payload of robot arm, there must be a way to take into account the dynamic cutting force. Some problems that are possible during robot machining are discussed, and some solution are proposed. Because milling force is not constant and still subsequently changes value and direction, it can be the source of vibration. Small stiffness of robot arm combined with vibrations can caused losing of robot position and improper surface after machining. Other problem can be robot programming for machining of curved surfaces in 3 dimensional space. There are same CAM system that can be used for that purpose. Results obtained with developed model can be used for design of robotic cell for chamfering and milling.   Normal 0 21 false false false PL X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:Standardowy; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";}

Auto-Calibration for Vision-Based 6-D Sensing System to Support Monitoring and Health Management for Industrial Robots

2021 ◽  
Author(s):  
Guixiu Qiao ◽  
Guangkun Li
Keyword(s):  
High Precision ◽  
Health Management ◽  
Calibration Method ◽  
Industrial Robots ◽  
Smart Manufacturing ◽  
Robot Arm ◽  
Sensing System ◽  
Robot Accuracy ◽  
Robot Machining ◽  
Machining Robot

Abstract Industrial robots play important roles in manufacturing automation for smart manufacturing. Some high-precision applications, for example, robot drilling, robot machining, robot high-precision assembly, and robot inspection, require higher robot accuracy compared with traditional part handling operations. The monitoring and assessment of robot accuracy degradation become critical for these applications. A novel vision-based sensing system for 6-D measurement (six-dimensional x, y, z, yaw, pitch, and roll) is developed at the National Institute of Standards and Technology (NIST) to measure the dynamic high accuracy movement of a robot arm. The measured 6-D information is used for robot accuracy degradation assessment and improvement. This paper presents an automatic calibration method for a vision-based 6-D sensing system. The stereo calibration is separated from the distortion calibration to speed up the on-site adjustment. Optimization algorithms are developed to achieve high calibration accuracy. The vision-based 6-D sensing system is used on a Universal Robots (UR5) to demonstrate the feasibility of using the system to assess the robot’s accuracy degradation.

scholarly journals A Soft Master-Slave Robot Mimicking Octopus Arm Structure Using Thin Artificial Muscles and Wire Encoders

Actuators ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 40 ◽  
Author(s):  
Shota Furukawa ◽  
Shuichi Wakimoto ◽  
Takefumi Kanda ◽  
Hiroki Hagihara
Keyword(s):  
Soft Materials ◽  
Industrial Robots ◽  
Artificial Muscles ◽  
Soft Robot ◽  
Robot Arm ◽  
Agricultural Field ◽  
Robot System ◽  
Pneumatic Artificial Muscles ◽  
High Degree ◽  
Rigid Skeleton

An octopus arm with a flexible structure and no rigid skeleton shows a high degree of freedom and flexibility. These excellent features are suitable for working in an environment having fragile and unknown-shaped objects. Therefore, a soft robot arm resembling an octopus arm can be useful as a harvesting machine without damaging crops in the agricultural field, as a rehabilitation apparatus in the welfare field, as a safe surgery tool in the medical field, and so on. Unlike industrial robots, to consider the applications of the soft robot arm, the instructions for it relating to a task cannot in many cases be given as a numerical value, and the motion according to an operator’s sense and intent is useful. This paper describes the design and feedback control of a soft master-slave robot system. The system is configured with two soft rubber machines; one is a slave machine that is the soft robot arm mimicking the muscle arrangement of the octopus arm by pneumatic artificial muscles, and the other is a master machine that gives the target motion to the slave machine. Both are configured with soft materials. The slave machine has an actuating part and a sensing part, it can perform bending and torsional motions, and these motions are estimated by the sensing part with threads that connect to wire encoders. The master machine is almost the same configuration, but it has no actuating part. The slave machine is driven according to the deformation of the master machine. We confirmed experimentally that the slave machine followed the master machine that was deformed by an operator.

Trajectory Planning for Conformal 3D Printing Using Non-Planar Layers

2018 ◽  
Author(s):  
Aniruddha V. Shembekar ◽  
Yeo Jung Yoon ◽  
Alec Kanyuck ◽  
Satyandra K. Gupta
Keyword(s):  
Additive Manufacturing ◽  
Trajectory Planning ◽  
Industrial Robots ◽  
Complex Geometries ◽  
Robot Arm ◽  
Joint Movement ◽  
Tool Orientation ◽  
3D Objects ◽  
Planar Surfaces ◽  
Build Time

Additive manufacturing (AM) technologies have been widely used to fabricate 3D objects quickly and cost-effectively. However, building parts consisting of complex geometries with multiple curvatures can be a challenging process for the traditional AM system whose capability is restricted to planar-layered printing. Using 6-DOF industrial robots for AM overcomes this limitation by allowing materials to deposit on non-planar surfaces with desired tool orientation. In this paper, we present collision-free trajectory planning for printing using non-planar deposition. Trajectory parameters subject to surface curvature are properly controlled to avoid any collision with printing surface. We have implemented our approach by using a 6-DOF robot arm. The complex 3D structures with various curvatures were successfully fabricated, while avoiding any failures in joint movement, holding comparable build time and completing with a satisfactory surface finish.

scholarly journals Detachable Robotic Grippers for Human-Robot Collaboration

2021 ◽  
Vol 8 ◽  
Author(s):  
Zubair Iqbal ◽  
Maria Pozzi ◽  
Domenico Prattichizzo ◽  
Gionata Salvietti
Keyword(s):  
Degrees Of Freedom ◽  
Tactile Feedback ◽  
Industrial Robots ◽  
Physical Interaction ◽  
Robot Arm ◽  
Robotic Hands ◽  
End Effector ◽  
External Power ◽  
Self Powered ◽  
Automatic Tool

Collaborative robots promise to add flexibility to production cells thanks to the fact that they can work not only close to humans but also with humans. The possibility of a direct physical interaction between humans and robots allows to perform operations that were inconceivable with industrial robots. Collaborative soft grippers have been recently introduced to extend this possibility beyond the robot end-effector, making humans able to directly act on robotic hands. In this work, we propose to exploit collaborative grippers in a novel paradigm in which these devices can be easily attached and detached from the robot arm and used also independently from it. This is possible only with self-powered hands, that are still quite uncommon in the market. In the presented paradigm not only hands can be attached/detached to/from the robot end-effector as if they were simple tools, but they can also remain active and fully functional after detachment. This ensures all the advantages brought in by tool changers, that allow for quick and possibly automatic tool exchange at the robot end-effector, but also gives the possibility of using the hand capabilities and degrees of freedom without the need of an arm or of external power supplies. In this paper, the concept of detachable robotic grippers is introduced and demonstrated through two illustrative tasks conducted with a new tool changer designed for collaborative grippers. The novel tool changer embeds electromagnets that are used to add safety during attach/detach operations. The activation of the electromagnets is controlled through a wearable interface capable of providing tactile feedback. The usability of the system is confirmed by the evaluations of 12 users.

Self-Calibration of Eye-to-Hand and Workspace for Mobile Service Robot

2012 ◽  
pp. 229-246
Author(s):  
Jwu-Sheng Hu ◽  
Yung-Jung Chang
Keyword(s):  
Visual Information ◽  
Calibration Method ◽  
Industrial Robots ◽  
Service Robots ◽  
Service Robot ◽  
Mobile Service ◽  
Robot Arm ◽  
Self Calibration ◽  
Laser Distance Sensor ◽  
Distance Sensor

The geometrical relationships among robot arm, camera, and workspace are important to carry out visual servo tasks. For industrial robots, the relationships are usually fixed and well calibrated by experienced operators. However, for service robots, particularly in mobile applications, the relationships might be changed. For example, when a mobile robot attempts to use the visual information from environmental cameras to perform grasping, it is necessary to know the relationships before taking actions. Moreover, the calibration should be done automatically. This chapter proposes a self-calibration method using a laser distance sensor mounted on the robot arm. The advantage of the method, as compared with pattern-based one, is that the workspace coordinate is also obtained at the same time using the projected laser spot. Further, it is not necessary for the robot arm to enter the view scope of the camera for calibration. This increases the safety when the workspace is unknown initially.

A SAW Mechanism for Investigating the Status of Industrial Robots Under Comprehensive Sustainable Aspects

2019 ◽  
Vol 10 (3) ◽  
pp. 69-84
Author(s):  
Atul Kumar Sahu ◽  
Harendra Kumar Narang ◽  
Mridul Singh Rajput ◽  
Nitin Kumar Sahu
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Industrial Robots ◽  
Fuzzy Sets Theory ◽  
Linguistic Terms ◽  
Fuzzy Concept ◽  
Course Of Action ◽  
The Status ◽  
Sets Theory ◽  
Robot Selection

The authors attempt to model a decision-making mechanism; which can fix multiple robot characteristics and can aid in investigating robots status for a particular manufacturing arena. The work exposed a series of applicable robot characteristics; which differentiated their working capacity and defines their value. A simple additive weighting (SAW) mechanism under a fuzzy concept is presented for investigating the status of industrial robots; which incorporates comprehensive aspects for sustainable robot selection. The authors have extended the application field of fuzzy sets theory and illustrated the significant application of linguistic terms in the robot decision-making problem. The work compounds fuzzy sets theory with SAW techniques and thus serves a flavor of fuzzy concept and a SAW technique under single platform. The study reveals the course of action for executing the proposed work by the managers. The work has applied fuzzy linguistic terms for griping the appropriate perceptions of the decision makers and applied the conception of SAW methodology to yield the decision results.

scholarly journals Modified Mechanistic Model Based on Gaussian Process Adjusting Technique for Cutting Force Prediction in Micro-End Milling

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Xiaoping Liao ◽  
Zhenkun Zhang ◽  
Kai Chen ◽  
Kang Li ◽  
Junyan Ma ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Cutting Force ◽  
Cutting Forces ◽  
End Milling ◽  
Mechanistic Model ◽  
Machining Process ◽  
Mechanistic Models ◽  
Machining Processes ◽  
Model Based ◽  
Micro End Milling

Micro-end milling is in common use of machining micro- and mesoscale products and is superior to other micro-machining processes in the manufacture of complex structures. Cutting force is the most direct factor reflecting the processing state, the change of which is related to the workpiece surface quality, tool wear and machine vibration, and so on, which indicates that it is important to analyze and predict cutting forces during machining process. In such problems, mechanistic models are frequently used for predicting machining forces and studying the effects of various process variables. However, these mechanistic models are derived based on various engineering assumptions and approximations (such as the slip-line field theory). As a result, the mechanistic models are generally less accurate. To accurately predict cutting forces, the paper proposes two modified mechanistic models, modified mechanistic models I and II. The modified mechanistic models are the integration of mathematical model based on Gaussian process (GP) adjustment model and mechanical model. Two different models have been validated on micro-end-milling experimental measurement. The mean absolute percentage errors of models I and II are 7.76% and 6.73%, respectively, while the original mechanistic model’s is 15.14%. It is obvious that the modified models are in better agreement with experiment. And model II performs better between the two modified mechanistic models.

Experimental and Analytical Study of Micro-Serrations on Surgical Blades

2015 ◽  
Author(s):  
Marco Giovannini ◽  
Newell Moser ◽  
Kornel Ehmann
Keyword(s):  
Finite Element ◽  
Laser Ablation ◽  
Cutting Force ◽  
Human Skin ◽  
Finite Element Methods ◽  
Analytical Study ◽  
Soft Materials ◽  
Blade Cutting ◽  
Cutting Behavior ◽  
Fundamental Objective

This paper reports on a study and application of laser ablation for machining of micro-serrations on surgical blades. The proposed concept is inspired by nature and mimics a mosquito’s maxilla, which is characterized by a number of serrations along its edge in order to painlessly penetrate human skin and tissue. The focus of this study is to investigate the maxilla’s penetration mechanisms and its application to commercial surgical blades. The fundamental objective is to understand the friction and cutting behavior between a serrated hard surface and soft materials, as well as to identify serration patterns that would minimize the cutting force and the friction of the blade during tissue cutting. Micro-serrations characterized by different patterns and sizes ranging from 200 μm to 400 μm were designed and manufactured on surgical blades. As supported by finite element methods (FEM), a reduction of 20∼30% in the force during blade cutting has been achieved, which encourages further studies and their applications to biomedical devices.

Regulation of 3D Human Arm Impedance Through Muscle Co-Contraction

2013 ◽  
Author(s):  
Harshil Patel ◽  
Gerald O’Neill ◽  
Panagiotis Artemiadis
Keyword(s):  
Dimensional Space ◽  
Human Subjects ◽  
Three Dimensional ◽  
Mechanical Impedance ◽  
Dominant Factor ◽  
Robot Arm ◽  
End Point ◽  
Human Arm ◽  
Arm Muscles ◽  
Experimental Trials

Humans have the inherent ability of performing highly dexterous and skillful tasks with their arms, involving maintenance of posture, movement, and interaction with the environment. The latter requires the human to control the dynamic characteristics of the upper limb musculoskeletal system. These characteristics are quantitatively represented by inertia, damping, and stiffness, which are measures of mechanical impedance. Many previous studies have shown that arm posture is a dominant factor in determining the end point impedance on a horizontal (transverse) plane. This paper presents the characterization of the end point impedance of the human arm in three-dimensional space. Moreover, it models the regulation of the arm impedance with respect to various levels of muscle co-contraction. The characterization is made by route of experimental trials where human subjects maintained arm posture while their arms were perturbed by a robot arm. Furthermore, the subjects were asked to control the level of their arm muscles’ co-contraction, using visual feedback of their muscles’ activation, in order to investigate the effect of this muscle co-contraction on the arm impedance. The results of this study show a very interesting, anisotropic increase of arm stiffness due to muscle co-contraction. These results could lead to very useful conclusions about the human’s arm biomechanics, as well as many implications for human motor control-specifically the control of arm impedance through muscle co-contraction.

PREDICTING UNKNOWN MOTION FOR MODEL INDEPENDENT VISUAL SERVOING

2001 ◽  
Vol 01 (03) ◽  
pp. 287-302 ◽  
Author(s):  
PATRICE WIRA ◽  
JEAN-PHILIPPE URBAN
Keyword(s):  
Kalman Filter ◽  
Time Delay ◽  
Real Time ◽  
Visual Servoing ◽  
Dimensional Space ◽  
Tracking Error ◽  
State Model ◽  
Divide And Conquer ◽  
Image Feature ◽  
Robot Arm

Prediction in real-time image sequences is a key-feature for visual servoing applications. It is used to compensate for the time-delay introduced by the image feature extraction process in the visual feedback loop. In order to track targets in a three-dimensional space in real-time with a robot arm, the target's movement and the robot end-effector's next position are predicted from the previous movements. A modular prediction architecture is presented, which is based on the Kalman filtering principle. The Kalman filter is an optimal stochastic estimation technique which needs an accurate system model and which is particularly sensitive to noise. The performances of this filter diminish with nonlinear systems and with time-varying environments. Therefore, we propose an adaptive Kalman filter using the modular framework of mixture of experts regulated by a gating network. The proposed filter has an adaptive state model to represent the system around its current state as close as possible. Different realizations of these state model adaptive Kalman filters are organized according to the divide-and-conquer principle: they all participate to the global estimation and a neural network mediates their different outputs in an unsupervised manner and tunes their parameters. The performances of the proposed approach are evaluated in terms of precision, capability to estimate and compensate abrupt changes in targets trajectories, as well as to adapt to time-variant parameters. The experiments prove that, without the use of models (e.g. the camera model, kinematic robot model, and system parameters) and without any prior knowledge about the targets movements, the predictions allow to compensate for the time-delay and to reduce the tracking error.

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