Remote Operation Server Skill-Based Video Adaptation
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Solution Overview
Problem
Existing systems for remotely operating work machines face challenges in reducing data communication load while ensuring operators can adequately grasp the machine's environment, particularly when the remote operation skill level and work content difficulty vary.
Innovation Solution
A remote operation server that recognizes the remote operation skill level and work content difficulty of each operator, allocates communication resources accordingly, and adjusts environment information factors to reduce data amounts while maintaining an appropriate information level for operators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If video information is limited or selectively provided to reduce data communication load, then data communication load is reduced, but operator's ability to grasp work machine environment deteriorates
Solution Approach 1:
The patent applies local quality by providing different video quality levels to different operators based on their skill levels. Experienced operators receive lower quality video (reducing communication load), while novice operators receive higher quality video (maintaining environment awareness). This resolves the contradiction by making video quality local to each operator's needs rather than uniform for all.
Solution Approach 2:
The patent implements dynamics by dynamically adjusting video quality parameters (resolution, frame rate, compression level) based on real-time assessment of operator skill level and current work conditions. The system continuously adapts the information provided to match the operator's evolving competence and the specific task requirements, balancing communication load reduction with environment information preservation.
2Loss of energy
If video quality is reduced for all operators, then data communication load is reduced, but novice operators cannot adequately grasp the work machine environment
Solution Approach 1:
The system applies local quality by segmenting operators into different skill groups and providing differentiated video quality levels. Novice operators receive high-quality video with minimal compression to ensure accurate environment perception, while experienced operators receive lower quality video. This resolves the contradiction by applying quality reduction locally only where it does not compromise reliability.
Solution Approach 2:
The patent segments the operator population into multiple skill levels and applies different video quality settings to each segment. This segmentation allows the system to maintain high reliability for novice operators while reducing communication load for experienced operators, thereby resolving the contradiction between load reduction and reliability maintenance.
3Loss of information
If high quality video is provided to all operators, then environment information is preserved, but data communication load increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting video parameters (resolution, frame rate, bit rate, compression level) based on operator skill level assessments. For experienced operators, parameters are reduced to minimize communication load, while for novice operators, parameters are maintained at high levels to preserve environment information. This resolves the contradiction by making parameter optimization conditional on operator capability.
Solution Approach 2:
The system implements dynamics by continuously monitoring operator performance and skill development, then dynamically adjusting video quality parameters accordingly. As operators gain experience, the system gradually reduces video quality parameters, optimizing the balance between information preservation and communication load reduction over time.
4Loss of energy
If video information is selectively provided based on operator skill level, then data communication load is optimized, but system complexity increases
Solution Approach 1:
The patent applies self-service by implementing automated skill level assessment and video quality adjustment systems. The system automatically evaluates operator performance, determines appropriate skill levels, and configures video parameters without manual intervention. This automation reduces the operational complexity of managing differentiated video streams, resolving the contradiction between optimization and complexity.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor operator performance and use this information to automatically adjust video quality settings. The feedback loop enables the system to self-optimize video parameters based on actual operator needs, reducing the complexity of manual configuration while maintaining optimized communication load and information quality.
Data Source
AI summary
According to the remote operation system or a remote operation server 20 included in the remote operation system, a “communication resource allocation process” is performed according to the skill or the like of the operator to allocate communication resources to a plurality of remote operation devices 10. When the “environment information control process” is performed, a data amount of environment data is reduced such that a reduction in the information amount of one or a plurality of low environment information factors is greater than the reduction in the information amount of one or a plurality of high environment information factors (meaning the reduction in the information amount of the environment information due to a change in the environment information factor). The environment information control process is performed in different modes according to a difference in an allocation resource.