Simulation based analysis of elastic multi-arm robot control in cooperative motion: dynamic model formulation

1993 ◽  
pp. 925-930
Author(s):  
Mikhail M. Svinin ◽  
Hartmut Bruhm ◽  
Henning Tolle
Keyword(s):  
Dynamic Model ◽  
Robot Control ◽  
Model Formulation ◽  
Cooperative Motion ◽  
Simulation Based

Temporally Consistent Simulation of Robots and Their Controllers

2014 ◽  
Author(s):  
James R. Taylor ◽  
Evan M. Drumwright ◽  
Gabriel Parmer
Keyword(s):  
Real Time ◽  
Collision Detection ◽  
Robot Control ◽  
Status Quo ◽  
Robot Dynamics ◽  
Control Software ◽  
Physical Systems ◽  
Detection Algorithms ◽  
Simulation Based ◽  
The Status

Researchers simulate robot dynamics to optimize gains, trajectories, and controls and to validate proper robot operation. In this paper, we focus on this latter application, which allows roboticists to verify that robots do not damage themselves, the environments they are situated within, or humans. In current simulations, robot control code runs in lockstep with the dynamics integration. This design can result in code that appears viable in simulation but runs too slowly on physical systems. Addressing this problem requires overcoming significant challenges that arise due both to the speed of dynamic simulation running time (simulations may run 1/10 or 1/100 of real-time or slower) and to the variability of the running times (e.g., the speed of collision detection algorithms depends on pairwise object proximities). These difficulties imply that one must not only slow the control software but also scale controller running speeds dynamically. We describe the numerous architectural and OS-level technical challenges that we have overcome to yield temporally consistent simulation for modeling robots that use only real-time processes, and we show that our system is superior to the status quo using simulation-based experiments.

Stochastic Model Bias Correction of Dynamic System Responses for Simulation-Based Reliability Analysis

2015 ◽  
Author(s):  
Zhimin Xi ◽  
Hao Pan ◽  
Ren-Jye Yang
Keyword(s):  
Stochastic Model ◽  
Dynamic System ◽  
Simulation Model ◽  
Reliability Analysis ◽  
Dynamic Model ◽  
Bias Correction ◽  
Simulation Models ◽  
Model Bias ◽  
Thermal Problem ◽  
Simulation Based

Reliability analysis based on the simulation model could be wrong if the simulation model were not validated. Various model bias correction approaches have been developed to improve the model credibility by adding the identified model bias to the baseline simulation model. However, little research has been conducted for simulation models with dynamic system responses. This paper presents such a framework for model bias correction of dynamic system responses for reliability analysis by addressing three technical components including: i) a validation metric for dynamic system responses, ii) an effective approach for dynamic model bias calibration and approximation, and iii) reliability analysis considering the dynamic model bias. Two case studies including a thermal problem and a corroded beam problem are employed to demonstrate the proposed approaches for simulation-based reliability analysis.

Unified Robot Control Scheme for Cooperative Motion, Autonomous Motion and Contact Reaction

2011 ◽  
Vol 23 (4) ◽  
pp. 557-566 ◽  
Author(s):  
Vincent Duchaine ◽  
◽  
Clément Gosselin ◽  
Keyword(s):  
Robot Control ◽  
Human Robot Interaction ◽  
Future Generations ◽  
Admittance Control ◽  
Robot Interaction ◽  
Modes Of Operation ◽  
Cooperative Motion ◽  
Control Scheme ◽  
Industrial Manipulators ◽  
Autonomous Motion

While the majority of industrial manipulators currently in use only need to performautonomousmotion, future generations of cooperative robots will also have to execute cooperative motion and intelligently react to contacts. These extended behaviours are essential to enable safe and effective physical Human-Robot Interaction (pHRI). However, they will inevitably result in an increase of the controller complexity. This paper presents a single variable admittance control scheme that handles the three modes of operation, thereby minimizing the complexity of the controller. First, the adaptative admittance controller previously proposed by the authors for cooperative motion is recalled. Then, a novel implementation of variable admittance control for the generation of smooth autonomous motion including reaction to collisions anywhere on the robot is presented. Finally, it is shown how the control equations for these three modes of operation can be simply unified into a unique control scheme.

A Unified Dynamic Model Formulation for Robotic Manipulator Systems

2003 ◽  
Vol 20 (10) ◽  
pp. 601-620
Author(s):  
Anjan Kumar Swain ◽  
Alan S. Morris
Keyword(s):  
Dynamic Model ◽  
Robotic Manipulator ◽  
Model Formulation

Simplified Dynamic Model for Amount of Directional Correction of Small-Diameter Tunneling Robot

1992 ◽  
Vol 114 (3) ◽  
pp. 476-480 ◽  
Author(s):  
Shin-ichi Aoshima ◽  
Tetsuro Yabuta
Keyword(s):  
Automatic Control ◽  
Dynamic Model ◽  
Robot Control ◽  
Small Diameter ◽  
Control Technology ◽  
Control Laws ◽  
Telecommunication Cable ◽  
Fluid Jets ◽  
Direction Control ◽  
Dynamic Simulator

In the last decade, small-diameter tunneling technology has improved considerably. As a result, the use of this technology is expected to increase dramatically [1]. For example, one microtunneling system can produce microtunnels ranging in diameter from 45 to 150 mm by using mechanically assisted high-pressure, low-volume fluid jets [2]. However, no dynamic model or automatic direction control has yet been designed for this technology. This paper describes a simplified dynamic model for the amount of vertical directional correction for a small-diameter tunneling robot designed to install telecommunication cable conduit. This model can also be used for the horizontal direction. The direction control of a tunneling robot conventionally depends on both the experience and intuition of the operator, and there have been no studies with regard to its automation. Therefore, in order to establish an automatic control technology for a small-diameter tunneling robot, we construct a simplified dynamic model for the amount of directional correction of the robot taking its past trajectory into consideration. We can make a dynamic simulator for the tunneling robot using this dynamic model. With this simulator, we can establish control laws for robot control. So, this study can contribute to the development of automatic control technology for a tunneling robot.

Verification of a Dynamic Grinding Model

1988 ◽  
Vol 110 (4) ◽  
pp. 403-409 ◽  
Author(s):  
T. R. Kurfess ◽  
D. E. Whitney ◽  
M. L. Brown
Keyword(s):  
Dynamic Model ◽  
Force Feedback ◽  
Intelligent System ◽  
Industrial Robot ◽  
Final Height ◽  
Feedback System ◽  
Weld Bead ◽  
Simulation Based ◽  
Measured Profile ◽  
Process Behavior

Many applications of industrial robot automation can be made possible or improved with the introduction of a force feedback system. The task of weld bead removal is being studied in an effort to develop a real time force controlled intelligent system. The process of weld bead grinding must be analyzed and modelled to develop a weld bead removal system. Previous research has developed and verified static models of grinding. This paper describes a dynamic model developed from the grinding characteristics demonstrated previously. An experimental grinding system was built and the measured process behavior was compared with a grinding simulation based on the dynamic model. The profile of the specimen was measured prior to and subsequent to grinding. The initial profile was used as an input to the simulation, and the output from the simulation was compared with the final measured profile. A variety of conditions was tested. For typical mean cut depths of 0.10 mm the simulator predicted the final height of the grinding specimen within a standard deviation of 0.02 mm. The dynamic model was verified within 10 percent of the actual results.

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