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Revision as of 09:59, 25 December 2012

FIDELIO: FIxtureless DEburring of wheeLs by human demonstratIOn

The experimental setup

Modern industrial robots are complex and powerful machines, able to execute a wide range of different tasks with high speed and accuracy. Nevertheless, they still have a low degree of autonomy and adaptability, and need a human operator to learn new tasks or tune existing ones.

In the last twenty years robotic researchers have been focusing on the Learning From Observation paradigm, developing prototypic robotic systems able to observe and learn from human operations. In this new paradigm, the information coming from a range of observations is analysed and transformed into an abstract representation of the task. By using such information, and exploiting the abstraction capabilities of a suitable cognitive system, the robot is able to autonomously generate a program to reproduce the task, even if the environment is different from the one observed during the learning phase.

The experimental setup

The FIDELIO project aims at researching into the feasibility (and the related advantages) of this innovative approach in an industrial application scenario, exemplified by a fixtureless wheel deburring task. To this end, a robotised cell has be set up, composed of a Comau SmartSix industrial manipulator and a workstation where aluminium wheels are placed for deburring. On top of the workstation a camera frames the workspace in order to locate the wheel. The arm is equipped with a pneumatic deburring tool connected to the robot end-effector through a force/torque sensor. In addition, an eye-in-hand camera is mounted at the robot end-effector, framing the cutting tool and the deburring edge.

The experiment focused on three main topics: an innovative programming technique based on walk-through programming, an eye-in-hand inspection system to measure burrs characteristics, and a methodology to autonomously learn the deburring skill.

Walk-through programming

In the walk-through programming the human operator plays the role of a teacher that physically walks the robot through the desired path. Furthermore, in an industrial application, like metal finishing or spray painting, the physical interaction between the human operator and the robot should be conceived in such a way that the teacher has the impression to grab a real tool, e.g. a deburring tool or a spray gun, instead of the robot end-effector.

The role of the control system is thus to accommodate for the motion commanded by the teacher, mimicking the same dynamic behaviour of the real tool, i.e. behaving like a virtual tool that exhibits the same mechanical properties of the real tool. At the same time, the admittance controller allows to introduce two active safety tools that contribute to make human-robot interaction, during the programming operation, safe. On one hand, an adaptive nonlinear viscuous friction limits the maximum end-effector velocity. On the other hand, virtual fences create a separation between the human body and the robot work-space.

The walk-through programming has been implemented and tested on a Comau SmartSix industrial manipulator, equipped with an ATI 6-axis wrist force torque sensor, exploiting the open version of the COMAU C4G controller.

The tests revealed that one of the most challenging problem in walk-through programming is the execution of a motion keeping the tool in contact with an hard surface. In fact, when the operator grabs the tool his/her forces and moments are transmitted to the sensor, allowing him/her to walk the robot through the desired path. If the operator, however, brings the tool into contact with a hard surface, two phenomena can be observed. First, the transition between free motion and contact is characterised by impulsive forces that are obviously opposing the robot motion. Then, if a stable contact can be established, the sensor measures the combination of the operator and the contact surface reaction forces. As a consequence, using a single sensor, wherever it is mounted, allows to measure only the superposition of the operator and the contact forces, giving the control system an information that does not allow to react independently to each of them. Using two force/torque sensors is an obvious but problematic solution, at least from an industrial application point of view, due to the high cost of this device. Another solution that can be envisaged concerns the development of a hybrid impedance/force controller to independently control the free and constrained directions of motion during the contact phase.

An inspection system to characterise burrs

The inspection system

In order to measure the work-piece profile, determining the presence of burrs and measuring the length and depth of each burr, a visual triangulation system has been set up. The system is composed of a camera and a linear laser projector, whose pose with respect to the camera frame is determined through a calibration process.

The inspection device is mounted at the robot end-effector. A visual servoing algorithm allows to track the work-piece profile, so that the inspection can be automatically executed. The result of this process is a 3D profile of the deburring edge measured with an accuracy of a tenth of millimeter.

Autonomously learning the deburring skill

A deburring task can be completely specified considering a cutting path and a set of variables (feedrate, cutting pressure, etc.) that determine the amount of material removed by the tool. The learning problem can be thus decomposed into two sub-problems: path learning and deburring skill learning. The latter concerning the development of a policy to select the cutting variables in such a way to execute the machining process as fast and precise as possible.

The idea behind the path learning algorithm is the following: considering different work-pieces characterised by the same shape and dimension, and thus the same nominal path, but affected by burrs in different position and of different length/depth, one should be able to combine all the information collected on these work-pieces in order to recover the nominal path. In particular, assuming that the burrs act like small and randomly distributed disturbances on the nominal path, it can be reconstructed computing the mean or the median curve among all the available paths.

On the other hand,

QUADRIVIO

The popularity of the research on unmanned ground vehicles has been recently increasing due to their usefulness in different operating environments. Planetary explorations, search and rescue missions in hazardous areas, surveillance, humanitarian demining, as well as agriculture applications such as pruning vine and fruit trees, are examples of potential applications of autonomous vehicles in natural environments. Unlike indoor mobile robotics, where only flat terrains are considered, outdoor robotics deals with all possible natural terrains. The unstructured environment and the terrain roughness including moving obstacles and poorly traversable terrains make the problem extremely challenging. All-Terrain Vehicles (ATVs) are suitable to drive in outdoor environments and through poorly traversable terrains, and compared to other movile platforms can rive at higher speed. ATVs, however, are also characterised by poor stability, roll- and tip-over phenomena, and excessive side slip. Those being the main drawbacks of these vehicles. The QUADRIVIO project aims at developing a low-cost unmanned ground vehicle for search and rescue missions in hazardous areas, possibly after a natural disaster. To achieve this challenging goal the project develops:

• a virtual rider, a low-level stabilisation system, including roll/tip-over prevention and obstacle avoidance mechanisms, that makes the vehicle autonomous at least for short range navigation
• a path planner that finds the best path in presence of rough an sloping terrains, taking into account the vehicle kinematic and dynamic constraints
• an ATV tracking controller that, acting on steer, throttle and brakes, tracks the desired path, ensuring the vehicle stability

A further aim of the QUADRIVIO project is the development of an airdrop system to parachute the vehicle on the operating area when, due to a natural disaster, all the main roads have been seriously damaged.