
执行预先编程的拣选和放置程序
验证操作员的手势识别
将地图手势向量映射到运动坐标
验证协作安全边界状态
执行预先设定的取放任务

Ensure all prerequisites are met before initiating the pilot phase to guarantee system stability and safety compliance.
Verify bandwidth supports real-time video streaming without packet loss exceeding 50ms.
Validate ambient lighting conditions meet minimum lux requirements for optical sensors.
Confirm operators complete mandatory gesture recognition training modules.
Execute emergency stop tests using physical buttons and voice commands as fallback.
Ensure all biometric data processing complies with GDPR and local privacy regulations.
Document environmental variables including dust, humidity, and reflective surfaces affecting sensors.
Install units in controlled zones to validate gesture library accuracy against baseline operations.
Refine model parameters based on pilot feedback and integrate with legacy control systems.
Expand deployment across all production floors while monitoring system health metrics.
吞吐效率:每小时处理 500 个单位,所需的人工干预最小。
Multi-modal input processing combining optical and depth data for robust gesture recognition.
Localized inference engine minimizing latency for real-time robotic response.
Hard-coded safety protocols ensuring immediate stoppage on unrecognized gestures in hazardous zones.
Standardized RESTful endpoints for seamless connection with existing ERP and MES systems.
Performance degrades in low-light conditions or high-reflectivity environments requiring additional calibration.
System response must remain under 200ms to prevent operator confusion or safety risks.
Always maintain manual override capabilities if gesture recognition fails unexpectedly.
Schedule quarterly sensor cleaning and software updates to maintain accuracy rates above 98%.