scholarly journals Research on Collision Point Identification Based on Six-Axis Force/Torque Sensor

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhijun Wang ◽  
Lu Liu ◽  
Wenkai Yan ◽  
Jing He ◽  
Bingyan Cui ◽  
...  
Keyword(s):  
Body Surface ◽  
Collision Detection ◽  
Detection Algorithm ◽  
Sensor Data ◽  
Torque Sensor ◽  
Surface Geometry ◽  
Geometric Information ◽  
Collision Point ◽  
Sensor Reading ◽  
Robot Body

The collision detection algorithm of the robot body previously needed to rely on the surface geometry information of the colliding object and no deformation was allowed during the collision process. To solve this problem, a new robot body collision detection algorithm that uses the force information of the six-axis force/torque sensor at the base to self-constrain is proposed which does not rely on the geometric information of the colliding object surface, and the deformation also allows deformation during the collision. In terms of sensor data preprocessing, a gravity and dynamic force compensation algorithm for the six-axis force/torque sensor at the base is proposed to ensure that the reading of the six-axis force/torque sensor at the base always maintains the value of 0 when the robot is working. Then, the robot is considered to have collided with the outside world when the sensor reading exceeds the set threshold. And a precision factor is proposed to analyze the influence of force and collision distance on the accuracy of the algorithm. Finally, the new algorithm proposed in this paper is compared with the traditional algorithm that relies on the geometric information of the colliding body surface. The experimental results indicate that the accuracy of the collision point detection algorithm proposed in this paper is close to that of the traditional method, but it does not need to rely on the geometric information of the collision body surface, and there is no requirement for whether there is deformation during the contact process. It can be concluded that the collision distance is the most important factor affecting the accuracy of the algorithm, followed by the conclusion of the magnitude of the collision force through the calculation of the precision factor. The results show that this method can effectively detect the collision point of the machine body, and the maximum error at the farthest point of the robot is 8.712%, which lays a certain foundation for the subsequent research on human-machine collaboration in small collaborative robots.

Failure detection and isolation in robotic manipulators using joint torque sensors

Robotica ◽  
2009 ◽  
Vol 28 (4) ◽  
pp. 549-561 ◽  
Author(s):  
Mehrzad Namvar ◽  
Farhad Aghili
Keyword(s):  
Fault Detection ◽  
Degrees Of Freedom ◽  
Failure Detection ◽  
Detection Algorithm ◽  
Joint Torque ◽  
Position Sensor ◽  
Torque Sensor ◽  
Sensor Noise ◽  
Sensor Reading ◽  
6 Degrees Of Freedom

SUMMARYReliability of any model-based failure detection and isolation (FDI) method depends on the amount of uncertainty in a system model. Recently, it has been shown that the use of joint torque sensing results in a simplified manipulator model that excludes hardly identifiable link dynamics and other nonlinearities such as friction, backlash, and flexibilities. In this paper, we show that the application of the simplified model in a fault detection algorithm increases reliability of fault monitoring system against modeling uncertainty. The proposed FDI filter is based on a smooth velocity observer of degree 2n where n stands for the number of manipulator joints. No velocity measurement and assumptions on smoothness of faults are used in the fault detection process. The paper focuses on actuator faults and investigates the effect of torque sensor noise on threshold selection. The FDI filter is further improved to become robust against an unknown bias in torque sensor reading. The effect of position sensor noise together with position sensor faults are also investigated. Simulation example on a 6-degrees of freedom manipulator is carried out to illustrate the performance of the proposed FDI method.

Collision-Free Tool Path Generation for Five-Axis High Speed Machining

2011 ◽  
Vol 474-476 ◽  
pp. 961-966 ◽  
Author(s):  
Li Qiang Zhang ◽  
Min Yue
Keyword(s):  
Image Analysis ◽  
Collision Detection ◽  
High Speed ◽  
Tool Path ◽  
Geometric Model ◽  
High Speed Machining ◽  
Analysis Method ◽  
Geometric Information ◽  
Detection Approach ◽  
Five Axis

Collision detection is a critical problem in five-axis high speed machining. Using a combination of process simulation and collision detection based on image analysis, a rapid detection approach is developed. The geometric model provides the cut geometry for the collision detection and records a dynamic geometric information for in-process workpiece. For the precise collision detection, a strategy of image analysis method is developed in order to make the approach efficient and maintian a high detection precision. An example of five-axis machining propeller is studied to demonstrate the proposed approach. It has shown that the collision detection task can be achieved with a near real-time performance.

Using LBG quantization for particle-based collision detection algorithm

2006 ◽  
Vol 7 (7) ◽  
pp. 1225-1232 ◽  
Author(s):  
Nida Saenghaengtham ◽  
Pizzanu Kanongchaiyos
Keyword(s):  
Collision Detection ◽  
Detection Algorithm

Haptic Rendering: Practical Modeling and Collision Detection

1999 ◽  
Author(s):  
ZhuLiang Cai ◽  
John Dill ◽  
Shahram Payandeh
Keyword(s):  
Surgical Training ◽  
Collision Detection ◽  
Object Representation ◽  
Virtual Assembly ◽  
Detection Algorithm ◽  
Haptic Rendering ◽  
3D Object ◽  
Modeling Techniques ◽  
Simulation Results ◽  
Fast Collision

Abstract 3D collision detection and modeling techniques can be used in the development of haptic rendering schemes which can be used, for example, in surgical training, virtual assembly, or games. Based on a fast collision detection algorithm (RAPID) and 3D object representation, a practical haptic rendering system has been developed. A sub-system determines detailed collision information. Simulation results are presented to demonstrate the practicality of our results.

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