Remote Robot-Sensor Calibration Service: Towards Cyber Physical Robotics

Remote Robot-Sensor Calibration Service: Towards Cyber Physical Robotics

Tapio Heikkilä, Tuomas Seppälä, Timo Kuula, Hannu Karvonen
DOI: 10.4018/IJMDWTFE.2019010102
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Abstract

Cyber physical systems (CPSs) are integrating computation, networking, and physical processes. CPSs facilitate improvements especially for asset management. The authors have contributed to robot automation with CPS technologies by a pilot system to support setup and maintenance of sensor-based robot systems with remote calibration services. This paper has focused to support remotely-located technology specialists as well as local field personnel by appropriate user interface design. A design example is given for a remote robot-sensor calibration procedure. In the user interface design, the authors follow loosely the Ecological Interface Design (EID) approach.
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Introduction

There are varying interpretations of a Cyber-Physical System (CPS), depending on the taken perspective. The increasing connectivity and use of devices with electronics and software in various situations of our everyday life is referred to differently by various research communities such as the CPSs, Internet of Things (IoT), ubiquitous computing, and pervasive computing disciplines. Additionally, application domains, like smart cities or Industry 4.0 (CPS in manufacturing) (Törngren et al, 2016) define CPSs differently.

On a general level, CPSs can be seen as systems, which rely on the integration of computation, networking and physical processes (Khaitan & Mccalley, 2014). Close interaction between cyber and physical worlds poses several challenges in the design of CPSs. The events in the physical world need to link to the cyber world and the decision taken by the cyber world needs to be communicated to the physical world with both required accuracy and timing.

Remote services lay in the front line of utilizing industrial cyber-physical technologies. The ideas related to remotely controlled and autonomous technologies, as well as views towards CPS, date back to the early days of the 20th century. As Nicola Tesla debuted the wireless “remote control”, he saw his own mind and body as an automaton, reacting to external stimuli and situations and believing that one day it may be possible to provide a machine with its “own mind,” which can also act on environmental stimuli of its own accord (Turi, 2014).

In remote operation (i.e., teleoperation) a machine is operated from a distant location from which there is no direct human sensory contact to the machine (Sheridan, 1992). The development of modern remote operation or service systems started in the 1940s, when Goertz developed the first mechanically controlled master-slave teleoperator (Sheridan, 1989). In today’s remote operation solutions, the human operator relies on video camera feeds, sensors, and other technical means to receive information about the remotely operated machine and its environment. Remote operation is utilized especially in hazardous and safety-critical environments to improve, the human operator’s safety or the cost-efficiency of the work. Previously, a plethora of different teleoperation applications have been developed from remote mining (see, e.g., Hainsworth, 2001) to space operation systems (see, e.g., Sheridan, 1993).

Remote operation and services pose also some risks in safety-critical operations, especially from the human factors (HF) point of view. Karvonen et al., (2012) have studied these HF issues in connection to a container crane remote operation case. Firstly, there can be many visibility-related challenges to perceive the object environment at an appropriate level, because the remote operator is not on the spot of the operation observing everything naturally. Instead, the operator has to rely on limited 2D video feeds to see the object environment. In this way, it is not possible to achieve a stereoscopic view about the objects of the operation. Secondly, in addition to visual feedback, also haptic, auditory and other modalities cannot have as good feedback as on the spot of the operation. Therefore, the operator cannot feel and hear realistically what is happening in the object environment at a certain moment. Thirdly, although it is good to receive good quality data, like high-resolution video feeds from the remotely operated object environment, the system’s responsiveness should not be compromised by increasing delays in direct manipulation. This problem is common in settings where the operated machine is very far away from the remote operator, like in space or mining applications.

Some of nowadays’ remote services use existing and new technologies to support field engineers, irrespective of the location. Today’s remote services are driven by changing and growing needs of customers to improve the return on assets of the systems. Remote services should ensure that the best knowledge is in the right place, at the right time. However, when having a large variety of products, this can be a complex undertaking (Cheever & Schroeder, 2006).

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