Collaborative Robot Sensor Control for Dynamic Collision Avoidance
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Solution Overview
Problem
Existing robot control systems in coactivity with human operators or other robots reduce productivity due to statically defined force limits, which are not relevant for dynamic collisions and may not ensure total safety, especially when collisions involve moving individuals or prolonged low-force contacts that can cause significant trauma.
Innovation Solution
A method using a robot equipped with contact, proximity, and vision sensors to dynamically adjust its operation by obtaining maximum admissible force values, monitoring its environment, and reducing speed to a security speed when obstacles are detected, while implementing gravity compensation and calculating avoidance trajectories to prevent collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot operates with statically defined force limits (e.g., 150 N threshold), then operator safety is improved by preventing collisions, but productivity deteriorates due to frequent safety stops and reduced operational speed
Solution Approach 1:
The patent applies dynamics by transitioning from static force limits to dynamic adaptive control. The robot continuously monitors environmental context through sensors (vision, proximity, force) and adjusts its operational parameters in real-time. When no human is detected, the robot operates at full speed and force capacity. When a human is detected, the robot dynamically adapts by reducing speed, lowering force thresholds, or stopping, thereby maintaining safety without unnecessary productivity loss from static conservative limits
Solution Approach 2:
The patent implements feedback through a closed-loop control system that continuously monitors environmental conditions using vision sensors, proximity sensors, and force sensors. This feedback enables the robot to detect human presence, assess collision risk, and adjust its operational parameters accordingly. The system processes sensor data in real-time and modifies robot behavior dynamically, allowing high productivity during unattended operation while ensuring safety when humans are present
Solution Approach 3:
The patent applies parameter changes by dynamically modifying operational parameters (speed, force thresholds, safety margins) based on real-time environmental conditions. The robot adjusts these parameters according to detected human presence, proximity, and potential collision risks, rather than maintaining fixed conservative values. This enables optimal productivity when safe and appropriate safety measures when needed
2Reliability
If the robot reduces speed to safety speed to allow operator anticipation, then operator safety is improved, but productivity deteriorates due to reduced operational efficiency
Solution Approach 1:
The patent applies dynamics by making robot speed adaptive rather than statically reduced. The robot operates at full speed when the environment is clear and only reduces speed dynamically when human presence is detected. The speed reduction is contextual and temporary, allowing the robot to maintain high productivity during unattended operation while ensuring safety when humans are present through real-time speed adaptation based on sensor feedback
3Device complexity
If the robot uses a fixed force threshold (e.g., 150 N) for collision detection, then simple collision detection is achieved, but safety deteriorates because prolonged low-force contacts or dynamic collisions are not adequately detected
Solution Approach 1:
The patent applies segmentation by dividing the detection system into multiple independent sensor modules: vision sensors for early human detection, proximity sensors for distance measurement, and force sensors for contact detection. Each sensor type monitors different aspects of potential collisions and operates with its own thresholds and algorithms. This segmented approach allows comprehensive collision detection covering both high-force impacts and prolonged low-force contacts while maintaining manageable system complexity through modular design
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting force thresholds and detection parameters based on contextual information from vision and proximity sensors. Rather than using a fixed 150 N threshold, the system adapts force detection sensitivity according to detected human presence, proximity distance, and movement patterns. This enables reliable detection of both high-force collisions and prolonged low-force contacts by adjusting parameters in real-time based on environmental context
Data Source
AI summary
A method for controlling the operation of a robot within a system. The system includes the robot and sensors to analyze the concentric environment of the system. The sensors include a contact sensor, a proximity sensor and a vision and location sensor. For each of the axes of the robot, a maximum allowable force value is obtained. If the force on one of the axes of the robot is greater than the maximum value, the robot is stopped in its position. A concentric monitoring space or a security space is obtained as a function of the speed of the robot. The environment of the robot is monitored by the sensors. If the intrusion of an object is detected in the safe space of the robot, the maneuvering speed of the robot is gradually decreased to a safe speed. The process is repeated for the next axis of the robot.