Robotic Waypoint Generation for Dynamic Object-Relative Trajectories
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Solution Overview
Problem
Conventional robotic systems face challenges in dynamically updating trajectories to adapt to changing environments and objects, particularly in non-industrial settings like kitchens, where variables such as pot size, orientation, and location can significantly affect task execution, leading to inflexible and unreliable performance.
Innovation Solution
The implementation of a robotic system that uses onboard computing with sensors and machine learning to parameterize trajectories, allowing for dynamic updates based on detected object attributes and environmental changes, enabling the robotic system to adapt its motion paths to fit changing conditions without requiring user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional robotic systems use fixed trajectories, then the device complexity is reduced, but the adaptability to changing environments and objects deteriorates
Solution Approach 1:
The patent applies parameter changes by transforming fixed trajectories into parameterized trajectories that can dynamically adjust to object attributes. The system identifies objects in the environment, extracts their attributes (size, shape, position), and uses these attributes as parameters to modify trajectory characteristics. This allows the robotic system to adapt to changing environments without requiring complete reprogramming of trajectories.
Solution Approach 2:
The patent implements dynamics by making trajectories dynamic rather than static. The parameterized trajectories can be continuously updated based on real-time object detection and attribute extraction. The system dynamically reparents trajectories to new objects when objects are added or removed from the environment, enabling the robotic system to respond to environmental changes in real-time.
2Reliability
If the robotic system dynamically updates trajectories based on object attributes, then the reliability of task execution is improved, but the difficulty of detecting and measuring object parameters increases
Solution Approach 1:
The patent implements feedback by continuously detecting objects in the environment, extracting their attributes, and using this information to update trajectory parameters. The system monitors the environment for object changes (additions, removals, movements) and dynamically adjusts trajectories based on detected attribute changes. This closed-loop feedback mechanism ensures reliable task execution even when environmental conditions change.
Solution Approach 2:
The patent applies self-service by enabling the robotic system to automatically detect objects, extract their attributes, and update its own trajectories without external intervention. The system autonomously identifies when objects change in the environment and self-corrects its motion plans by reparenting trajectories to new objects or adjusting parameters based on detected attribute changes.
3Ease of operation
If the system uses parameterized trajectories with dynamic updates, then the ease of operation is improved, but the loss of time for processing and updating trajectories increases
Solution Approach 1:
The patent applies preliminary action by pre-defining trajectory templates and parameter relationships before execution. The system prepares parameterized trajectory structures in advance that can be quickly instantiated and adjusted based on detected object attributes. This preliminary preparation reduces the computational burden during real-time operation, minimizing trajectory update time while maintaining ease of operation.
Data Source
AI summary
In one embodiment, a method includes generating a trajectory plan to complete a task to be executed by a robotic system, identifying objects in the environment required for completing the task, determining attributes for each of the identified objects, determining trajectory-parameters for the trajectory plan based on the determined attributes for each identified object and operational conditions in an environment associated with the robotic system, and executing the task based on the determined trajectory-parameters for the trajectory plan.