2015

DOI: 10.1299/jsmermd.2015._2p1-d08_1

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2P1-D08 Study on Telexistence LXXXI : Effectiveness of Spatial Coherent Remote Driving Experience with a Telexistence Backhoe Under Hazardous Conditions

Charith Lasantha Fernando

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Mhd Yamen Saraiji

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et al.

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“…Reference [8], similar to our work, present results from remote-operation of an excavator over a wireless IP network. They use a head mount display (HMD) with end to end latency of 180 milliseconds and report 164% Related research on automatic bucket-filling is the work done on Load-haul-dump (LHD) machines, which are a variation of wheel-loaders adapted for underground mines.…”

Section: Related Workmentioning

confidence: 72%

From Tele-Remote Operation to Semi-Automated Wheel-Loader

et al. 2018

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This paper presents experimental results with tele-remote operation of a wheel-loader and proposes a way towards semi-automation. The different components of the tele-remote setup are described in the paper. Short loading cycle is an operation cycle, commonly used at quarry and construction sites for moving gravel from piles onto trucks. We present results from short loading cycle experiments with three operators comparing productivity between teleremote operation and manual operation. Productivity loss of 42% with tele-remote operation motivates the case for more automation. We propose a method to automate the bucketfilling step, which is one of the key functionality of a wheelloader.

“…Reference [8], similar to our work, present results from remote-operation of an excavator over a wireless IP network. They use a head mount display (HMD) with end to end latency of 180 milliseconds and report 164% Related research on automatic bucket-filling is the work done on Load-haul-dump (LHD) machines, which are a variation of wheel-loaders adapted for underground mines.…”

Section: Related Workmentioning

confidence: 72%

From Tele-Remote Operation to Semi-Automated Wheel-Loader

et al. 2018

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This paper presents experimental results with tele-remote operation of a wheel-loader and proposes a way towards semi-automation. The different components of the tele-remote setup are described in the paper. Short loading cycle is an operation cycle, commonly used at quarry and construction sites for moving gravel from piles onto trucks. We present results from short loading cycle experiments with three operators comparing productivity between teleremote operation and manual operation. Productivity loss of 42% with tele-remote operation motivates the case for more automation. We propose a method to automate the bucketfilling step, which is one of the key functionality of a wheelloader.

“…Remote-operated construction machinery is being tried for commercial purposes [13,14]. However, this has led to a greater reduction in productivity and fuel efficiency [15] than manual operation because there are not enough sensory inputs to the remote operators. Therefore, to increase the fuel efficiency and productivity of construction machinery, it is necessary to improve the degree of automation of the loader to reduce the operator's remote intervention.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Prediction of Throttle Value and State for Wheel Loaders

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et al. 2021

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Accurate prediction of the throttle value and state for wheel loaders can help to achieve autonomous operation, thereby reducing the cost and accident rate. However, existing methods based on a physical model cannot accurately reflect the operator’s driving habits and the interaction between wheel loaders and the environment. In this paper, a deep-learning-based prediction model is developed to predict the throttle value and state for wheel loaders by learning from driving data. Multiple long–short-term memory (LSTM) networks are used to extract the temporal features of different stages during the operation of the wheel loader. Two backward-propagation neural networks (BPNNs), which use the temporal feature extracted by LSTM as the input, are designed to output the final prediction results of throttle value and state, respectively. The proposed prediction model is trained and tested using the data from two different conditions. The end-to-end LSTM prediction model and BPNNs are used as benchmark models. The results indicate that the proposed prediction model has good prediction accuracy and adaptability. Furthermore, the relationship between the prediction performance and signal sampling frequency is also studied. The proposed prediction method that combines driving data and deep learning can make the throttle action conform to the decisions of an experienced operator, providing technical support for the autonomous operation of construction machinery.

“…In [6], the remote control of an excavator over a wireless IP network using a head mount display (HMD) with an end-to-end latency of 180 ms reports a 164% increase in the cycle time of operation time for remote control, compared to manual operation. The amount of tolerable latency for teleoperation varies a lot between different experiments, and the variation in latency (jitter) can be more detrimental to performance than the latency itself [7].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Video with SCReAM over LTE for Remote‐Operated Working Machines

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et al. 2018

Wireless Communications and Mobile Computing

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Remote operation is a step toward the automation of mobile working machines. Safe and efficient teleremote operation requires good-quality video feedback. Varying radio conditions make it desirable to adapt the video sending rate of cameras to make the best use of the wireless capacity. The adaptation should be able to prioritize camera feeds in different directions depending on motion, ongoing tasks, and safety concerns. Self-Clocked Rate Adaptation for Multimedia (SCReAM) provides a rate adaptation algorithm for these needs. SCReAM can control the compression used for multiple video streams using differentiating priorities and thereby provide sufficient congestion control to achieve both low latency and high video throughput. We present results from the testing of prioritized adaptation of four video streams with SCReAM over LTE and discuss how such adaptation can be useful for the teleremote operation of working machines.

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