Thursday 3 May 2012

"Teachingless" robotics projects...

In the case of conventional industrial robot systems, operators must write robot-language programs for each robot task by using hand-held "teach pendant" or off-line robot programming software. This process is long, tedious and requires technical experts in robot programming. Moreover, as each new robot motion needs a human action, the use of robots is restricted to repetitive tasks which need to be executed thousands of times. No variation around the recorded motion is allowed.

Performing numerous different tasks with the same flexible robot is becoming possible with "teachingless" solutions; opening new fields of use where programming the robot was economically not viable.

“Coupling hardware sensors to our automatic path planner software creates the bridge between virtual and real environments; robot motion is computed in the virtual representation of the real world and executed in this later without programming” says Laurent Maniscalco, Kineo CAM’s CEO; “as of today five of our customers have already or are currently developing teachingless robotic systems in the following fields: programming-less structural steel welding in North America, electronic assembly in Japan, automated part sorting in Germany or aircraft structure assembly control in France”.

Kineo CAM proposes a set of libraries to make industrial robots more autonomous, flexible and easy-to-use, extending the use of industrial robots to non-robotic experts for flexible tasks.

The software component named KineoWorks™ can be used offline within a dedicated system that will automatically compute the robot program before sending it to the shop floor. The automation of the programming permits quick reconfigurations of the robotic cell in a flexible manufacturing paradigm.

It can also be used online. Embedded on the system controlling the robot and coupled with a perception system (LIDAR, Structured light 3D scanner, computer vision...) and/or a Digital Mockup, it can automatically plan collision-free motion, control its execution, react to unexpected obstacles (moving object, worker, obstructed obstacle) and re-plan a detour on-the-fly. This is what we call reactive path planning:

A preliminary scanning of the environment allows planning an initial trajectory. Once the robot starts to execute the motion, KineoWorks™ continues to analyze the captured data as it comes in order to anticipate potential collisions. A continuous process tries to keep the obstacles away by deforming the trajectory. When the deformation fails, a new path planning is launched on-the-fly in parallel and without interrupting the ongoing motion.

Thanks to reactive and fast path planning, the robot can autonomously move in an unknown environment. In particular a project funded by the French government uses KineoWorks™ embedded into a UGV to explore unknown or “not well known” installations, such as a plant damaged by a natural disaster like an earthquake.

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