Optimizing the Robot Arm Movement Time Using Virtual Reality Robotic Teaching System

Abstract

Robots play an important role in performing operations such as welding, drilling and screwing parts in manufacturing. Optimizing the robot arm movement time between different points is an important task which will minimize the make-span and maximize the production rate. But robot programming is a complex task whereby the user needs to teach and control the robot in order to perform a desired action. In order to address the above problem, an integrated 3-dimensional (3D) simulation software and virtual reality (VR) system is developed to simplify and speed up tasks and therefore enhance the quality of manufacturing processes. This system has the capability to communicate, transfer, optimize and test the data obtained from the VR and 3D environment to the real robot in a fast and efficient manner. In addition, this system eliminates the need for robot programming, and thus it is easily implemented by users with limited engineering knowledge. The optimization model is tested on a test case, in which the data are extracted from the VR system. The results show an increase in production rate and a decrease in cycle time when the make-span is minimized. The virtual reality robotic teaching system (VRRTS) offers several benefits to users, and will therefore surpass complex and time-intensive conventional robot programming methods.

Skinner operant conditioning model and robot bionic self-learning control

“…Receive and analyze response of the twowheeled robot system to ak(t) and get increment of orientation value ( 1) t    with the rewarding rate.…”

“…Conditioned reflex of operation: with ( 1) ( ( ), ( ), ( )) P t a t t P t     and ( 1) ( ( 1), ( 1)) d t w t z t      , update the selection rate and the rewarding rate of operating behavior.…”

“…Otherwise, update time variable 1 t t   , and choose randomly a new fuzzy consequent behavior ( 1) k a t   according to updated probability vector P j (t+1) and repeat "Step.2 ÷ Step.5" until the optimal fuzzy consequent collection * A is achieved.…”

Implementation of Correlation Analysis to Work Sampling Results

“…Work sampling method is used for collection of empirical data. Although it is not the express purpose of work sampling to determine how long specific tasks should take, work sampling data, when coupled with historical production data for key volume indicators and performance levelling, can provide information that can be used to establish standards [6,7]. The major goal of work sampling, however, is to determine the proportion of the workday spent on certain types of work.…”

Robust Adaptive Position and Force Tracking Control Strategy for Door-Opening Behaviour

“…To complete the above operations, the optimized path planning should be considered first [22]. Only the path planning of the manipulator is considered in this study given that the vehicle remains still during the door-opening process.…”