Robot Collision Monitoring With Adaptive Axle Load Thresholds
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Solution Overview
Problem
The specification of limit values for deviations between actual and target axle loads in robot collision monitoring is complicated, and reliable detection of actual collisions is difficult due to varying environmental conditions and systematic errors, leading to potential unfounded responses.
Innovation Solution
A method that continuously monitors the actual axle load of a robot by determining deviations from a predicted reference value, using a moving average and sliding change in reference values to adapt the limit value, and switches between different operating modes based on speed to improve collision detection sensitivity and reduce false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed limit values are used for collision monitoring, then the system is simple to operate, but it produces false alarms due to varying environmental conditions and systematic errors
Solution Approach 1:
The patent implements dynamic limit values that automatically adapt to varying operating conditions such as temperature, humidity, and robot speed. Instead of using fixed threshold values, the system continuously adjusts limit values based on real-time environmental parameters and operational state, thereby maintaining high detection reliability without requiring manual recalibration for different conditions
Solution Approach 2:
The system incorporates feedback mechanisms that monitor actual axle loads and compare them against dynamically calculated limit values. The feedback loop continuously refines the limit values based on observed deviations and environmental conditions, enabling the system to learn from past operations and improve collision detection accuracy over time while reducing false alarms
2Measurement precision
If the limit value is set low to detect actual collisions, then collision detection sensitivity is improved, but false alarms increase due to systematic errors and environmental variations
Solution Approach 1:
The patent applies different limit values for different axes and different operating conditions rather than using a single global threshold. Each axis receives customized limit values based on its specific characteristics, payload, and environmental conditions, allowing high sensitivity for actual collision detection while accommodating systematic variations specific to each axis and condition
Solution Approach 2:
The system dynamically changes limit value parameters based on environmental conditions (temperature, humidity), robot operating parameters (speed, acceleration, payload), and historical operation data. This parameter adaptation enables the system to maintain optimal detection sensitivity across varying conditions while filtering out false alarms caused by environmental fluctuations
3Ease of operation
If manual specification of limit values is used, then the system is easy to understand, but it requires cumbersome adjustment for different conditions
Solution Approach 1:
The system performs self-adjustment of limit values based on environmental sensors, robot operational data, and historical collision information. The control unit automatically calculates and updates appropriate limit values without requiring manual intervention, making the system both easy to operate and highly adaptable to changing conditions simultaneously
Data Source
Figure 1~2
AI summary
A method according to the invention for collision monitoring of a robot (1) comprises the steps: - determining (S10) an actual value (T) of an axle load of at least one axle (A1- A6) of the robot and - identifying (S40) a collision of the robot if a deviation between said actual value and a reference value (Ts; TR) of the axle load exceeds a threshold value, wherein the threshold value is determined according to at least one preceding deviation between the actual and reference value and/or at least one preceding reference value and/or the reference value is determined according to a preceding actual value.