Robot Grasping Motion Path Selection for Calculation Efficiency
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Solution Overview
Problem
Current robots face challenges in stably grasping objects due to complex calculations for arm path planning and difficulty in grasping objects with obstacles, leading to inefficient grasping motions and potential failures.
Innovation Solution
A robot system that includes a database for storing grasping motions, an input unit for receiving object data, a grasping motion path generation unit to select suitable grasping motions based on object and obstacle positions, and an arm path generation unit to calculate and output torques for arm movement, allowing for adaptive and efficient grasping with the help of multiple hands if needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex path planning calculations are performed for arm movement, then grasping accuracy is improved, but calculation time increases
Solution Approach 1:
The system pre-calculates and stores multiple possible grasping motion paths and arm paths in a database before actual grasping operations. When a grasping task is executed, the controller retrieves pre-computed paths from the database rather than calculating them in real-time, significantly reducing calculation time while maintaining grasping accuracy through selection from pre-analyzed paths
Solution Approach 2:
The system dynamically selects appropriate grasping motion paths and arm paths from the database based on real-time conditions such as object position, obstacle locations, and hand positions. This dynamic selection approach allows the system to adapt to varying conditions without performing complex real-time calculations, balancing accuracy and speed
2Reliability
If multiple grasping motions are considered, then grasping reliability is improved, but system complexity increases
Solution Approach 1:
The grasping task is segmented into distinct components: multiple pre-defined grasping motion paths stored in the database, multiple pre-defined arm paths, and a controller that selects and coordinates these pre-segmented paths. This segmentation allows the system to consider multiple grasping motions for improved reliability while managing complexity through modular organization of paths and motions
Solution Approach 2:
The database acts as an intermediary between the multiple grasping motions and the controller. It stores and organizes numerous pre-calculated grasping motion paths and arm paths, allowing the controller to access and select from multiple options without directly managing the complexity of all possible motions. This intermediary structure enables reliable multi-path selection while keeping the control system manageable
3Reliability
If obstacle detection and avoidance are implemented, then grasping success rate is improved, but calculation complexity increases
Solution Approach 1:
The system pre-calculates multiple grasping motion paths and arm paths that inherently account for obstacle avoidance. These paths are stored in the database before execution, meaning obstacle detection and avoidance strategies are prepared in advance rather than computed in real-time during grasping operations, reducing calculation complexity while maintaining high success rates
Data Source
AI summary
A robot and a control method thereof. The control method includes generating and storing plural grasping motions corresponding to data of a target object, selecting a grasping motion corresponding to a grasping purpose of the target object among the plural grasping motions, generating a path of arms corresponding to the selected grasping motion, calculating torques to track the path of the arms, and outputting the torques toward the arms so as to perform movement of the arms and grasping of the target object. The grasping motion path corresponding to the grasping purpose is generated and the path of arms is generated, thereby reducing overall calculation time during grasping of the target object to increase calculating efficiency, minimizing generation of the path of the arms, and allowing an arm path calculating process to be performed at the late stage of a grasping control process to improve grasping performance.