Multi-Arm Robot Grasping Easiness Index Selection
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Solution Overview
Problem
Existing robot apparatuses with multiple arm sections struggle to dynamically select the most suitable arm for grasping objects in changing environments, often relying on fixed task designs and limited strategies that do not account for varying postures and obstacles.
Innovation Solution
A robot apparatus equipped with a grasping-easiness calculation section to quantify the ease of grasping for each arm section, and an arm-section selection section to choose the most suitable arm based on calculated index values, considering manipulability, joint range-of-motion, and interference possibilities with the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If an arm that is nearer to the object is used for grasping, then the operation is simpler and faster, but the grasping may fail when the object posture is fixed or there are obstacles
Solution Approach 1:
The patent changes the selection criterion from simple proximity to a comprehensive evaluation index that includes manipulability, joint range-of-motion, and interference possibility. This allows the system to select arms based on multiple parameters rather than just distance, resolving the contradiction between simple operation and reliable grasping.
Solution Approach 2:
The patent implements dynamic arm selection by continuously evaluating the grasping ease index based on current object posture and environmental conditions. Instead of fixed arm assignment, the system dynamically determines which arm is most suitable for each grasping task, adapting to changing circumstances.
2Device complexity
If tasks are fixedly assigned to each arm, then the control is simpler, but the robot cannot adapt to dynamically changing environments
Solution Approach 1:
The patent makes the arm assignment dynamic by calculating a grasping ease index for each arm based on current environmental conditions and object posture. This allows the robot to adapt to changing environments while maintaining relatively simple control logic through automated index-based selection.
Solution Approach 2:
The system performs self-evaluation of each arm's suitability for grasping by automatically calculating the grasping ease index. The robot determines its own optimal configuration without external intervention, balancing adaptability with operational simplicity.
3Measurement precision
If a quantitative evaluation of grasping ease is performed for each arm, then the arm selection is more accurate, but the calculation complexity increases
Solution Approach 1:
The patent evaluates multiple parameters (manipulability, joint range-of-motion, interference possibility) for each arm and combines them into a single grasping ease index. This quantitative approach provides accurate arm selection while managing complexity through systematic parameter integration.
Solution Approach 2:
The patent divides the evaluation into separate components (manipulability evaluation, joint range-of-motion evaluation, interference possibility evaluation) that are calculated independently and then combined. This segmentation makes the complex calculation process more manageable and computationally efficient.
Data Source
AI summary
A robot apparatus includes a plurality of arm sections; a grasping-easiness calculation section configured to calculate an index value of grasping easiness quantitatively evaluating easiness of assuming a grasping posture for grasping an object or assuming a transition posture leading to the grasping posture for each of the plurality of arm sections; and an arm-section selection section configured to select an arm section to be used for actually grasping the object on the basis of the index value of the grasping easiness calculated for each of the arm sections.