Spatial Programming for Industrial Robots through Task Demonstration

We present an intuitive system for the programming of industrial robots using markerless gesture recognition and mobile augmented reality in terms of programming by demonstration. The approach covers gesture-based task definition and adaption by human demonstration, as well as task evaluation through augmented reality. A 3D motion tracking system and a handheld device establish the basis for the presented spatial programming system. In this publication, we present a prototype toward the programming of an assembly sequence consisting of several pick-and-place tasks. A scene reconstruction provides pose estimation of known objects with the help of the 2D camera of the handheld. Therefore, the programmer is able to define the program through natural bare-hand manipulation of these objects with the help of direct visual feedback in the augmented reality application. The program can be adapted by gestures and transmitted subsequently to an arbitrary industrial robot controller using a unified interface. Finally, we discuss an application of the presented spatial programming approach toward robot-based welding tasks

VR-Based Robot Programming and Simulation System for an Industrial Robot

Traditional robot programming such as teach by lead etc have been used for many years. These methods are considered not efficient and outdated in the current industrial and market demands. In this paper, virtual reality (VR) technology is used to improve human-robot interface - no complicated command or programming knowledge is required. The system is divided into three major parts: task teaching by demonstration in a computer generated virtual environment, a graphical robot simulator with intelligent robot command generator and last but not least, real task execution. The user is requested to complete the desired task in a virtual teaching system by wearing a data glove attached with a sensor tracker. The process path will be simulated and analyzed to obtain the optimum trajectory. Robot motions can be checked through the simulation program and robot program can be generated for the real task execution

Sidebar- Programming Commercial Robots

P. 125-132Manual systems require the user/programmer to directly enter the desired behaviour of the robot, usually using a graphical or text-based programming language, as shown in Fig. 1. Text-based systems are either controller-specific languages, generic procedural languages, or behavioural languages, which typically differ by the flexibility and method of expression of the system. Graphical languages [BKS02, BI01] use a graph, flow-chart or diagram based graphical interface to programming, sacrificing some flexibility and expressiveness for ease of use. The user/programmer has little or no direct control over the robot code in an automatic programming system, which may acquire the program by learning, programming by demonstration (PbD), or by instruction, as indicated in Fig. 2. Often automatic systems are used “online,” with a running robot, although a simulation can also be used. In this sidebar we will focus on the characteristics of commercial programming environments. Simple robots can be programmed directly using their own operating systems. More sophisticated robots include SDKs to simplify the programming of their robots. Mobile robots programming environments vs. industrial manipulators are also presente

Optimizing Programming by Demonstration for in-contact task models by Incremental Learning

Despite the increasing usage of robots for industrial applications, many aspects prevent robots from being used in daily life. One of these aspects is that extensive knowledge in programming a robot is necessary to make the robot achieve a desired task. Conventional robot programming is complex, time consuming and expensive, as every aspect of a task has to be considered. Novel intuitive and easy to use methods to program robots are necessary to facilitate the usage in daily life. This thesis proposes an approach that allows a novice user to program a robot by demonstration and provides assistance to incrementally refine the trained skill. The user utilizes kinesthetic teaching to provide an initial demonstration to the robot. Based on the information extracted from this demonstration the robot starts executing the demonstrated task. The assistance system allows the user to train the robot during the execution and thus refine the model of the task. Experiments with a KUKA LWR4+ industrial robot evaluate the performance of the assistance system and advantages over unassisted approaches. Furthermore a user study is performed to evaluate the interaction between a novice user and robot

How to Deploy a Wire with a Robotic Platform: Learning from Human Visual Demonstrations

In this paper, we address the problem of deploying a wire along a specific path selected by an unskilled user. The robot has to learn the selected path and pass a wire through the peg table by using the same tool. The main contribution regards the hybrid use of Cartesian positions provided by a learning procedure and joint positions obtained by inverse kinematics and motion planning. Some constraints are introduced to deal with non-rigid material without breaks or knots. We took into account a series of metrics to evaluate the robot learning capabilities, all of them over performed the targets