Robotic Trajectory Planning Using Real-Time Object Metrics
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Solution Overview
Problem
Robotic systems face challenges in efficiently picking and moving objects with unknown dimensions or properties, as measurements are often taken after the object is lifted, leading to potential dropping or collision risks.
Innovation Solution
A combination of sensors, including depth sensors and force-torque sensors, is used to determine object metrics in real-time, allowing for preplanned and adaptive trajectory planning to ensure safe and efficient transport.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If measurements are taken after the object is lifted, then the robotic system can handle objects with unknown dimensions, but the risk of dropping or collision increases
Solution Approach 1:
The system performs preliminary measurements of object dimensions and properties using sensors (depth sensors, force-torque sensors, vision systems) before the robotic arm lifts the object. This allows the trajectory planning system to precalculate safe motion paths that account for the specific object characteristics, eliminating the need to measure after lifting and thereby preventing dropping or collision risks.
2Reliability
If real-time measurements are used for trajectory planning, then the safety and efficiency of object transport is improved, but the system complexity increases
Solution Approach 1:
The system divides the measurement and control process into separate modular components: depth sensors for dimensional measurement, force-torque sensors for weight and grip force monitoring, vision systems for object identification, and a trajectory planning module that processes sensor data. This segmentation allows each component to specialize in specific tasks, improving overall safety while making the complex system more manageable and maintainable.
3Measurement precision
If multiple sensors are used to determine object metrics, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The system integrates multiple sensor types (depth sensors, force-torque sensors, vision systems) into a unified measurement framework where sensor data is fused to comprehensively determine object dimensions, weight, and other metrics. This merging approach achieves high measurement precision by compensating for individual sensor limitations while the integrated architecture reduces overall complexity compared to separate independent systems.
Data Source
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AI summary
Example systems and methods may be used to determine a trajectory for moving an object using a robotic device. One example method includes determining a plurality of possible trajectories for moving an object with an end effector of a robotic manipulator based on a plurality of possible object measurements. The method may further include causing the robotic manipulator to pick up the object with the end effector. After causing the robotic manipulator to pick up the object with the end effector, the method may also include receiving sensor data from one or more sensors indicative of one or more measurements of the object. Based on the received sensor data, the method may additionally include selecting a trajectory for moving the object from the plurality of possible trajectories. The method may further include causing the robotic manipulator to move the object through the selected trajectory.