Robot Trajectory Control for Predictive Human Safety Distancing
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Solution Overview
Problem
Existing robot control systems face challenges in balancing safety and operational efficiency, often resulting in reduced productivity due to frequent stopping or unverified trajectory modifications, and struggle to meet safety standards when relying solely on machine learning.
Innovation Solution
A control device that includes a judgment unit to determine if the robot's movement trajectory needs to be modified based on predicted future positions of both the robot and a person, prioritizing stopping or deceleration when safety distances are breached, and resuming operation based on modified trajectories when safe distances are maintained.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot stops or decelerates when a person approaches within a predetermined distance, then safety is improved, but operational efficiency and productivity deteriorate due to frequent stopping
Solution Approach 1:
The prediction unit performs preliminary action by predicting future positions of both the robot and person before collision occurs. The modification unit then modifies the movement trajectory in advance to prevent potential collisions, allowing the robot to maintain motion rather than stopping reactively when distances become critical.
Solution Approach 2:
The system implements continuous feedback by repeatedly predicting future positions based on current positions and velocities, evaluating predicted distances against safety thresholds, and dynamically adjusting trajectories. This closed-loop control enables proactive safety management while maintaining operational flow.
2Productivity
If machine learning is used for robot control to improve operational efficiency, then productivity is improved, but meeting safety standards becomes difficult
Solution Approach 1:
The patent replaces machine learning-based control with deterministic mathematical prediction methods. By using explicit position and velocity calculations based on current state and trajectory information, the system achieves both high operational efficiency and provable safety compliance that can be verified through formal methods.
Solution Approach 2:
The system changes from probabilistic machine learning outputs to deterministic parameter-based predictions. By calculating future positions using current position, velocity, and trajectory parameters, the system maintains operational efficiency while producing predictable, verifiable results that satisfy safety certification requirements.
Data Source
AI summary
In a case in which a second distance between a future position of a robot and a future position of a person is shorter than a second predetermined distance, a modification unit modifies movement trajectory information such that the second distance is equal to or longer than the second predetermined distance. In a case in which a first distance is shorter than a first predetermined distance, a control unit stops or decelerates a movement of the robot, regardless of whether the movement trajectory information is modified. In a case in which the first distance is equal to or longer than the first predetermined distance and the movement trajectory information is modified, the control unit controls the movement of the robot on the basis of the movement trajectory information after modification.