Vision-Guided Soft Robotic Gripper for Adaptive Heterogeneous Grasping
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Solution Overview
Problem
Conventional robotic grippers are specific to certain types of objects, requiring frequent changes and maintenance due to their inability to adapt to diverse shapes and textures, leading to inefficiencies in handling heterogeneous items.
Innovation Solution
A reconfigurable soft robotic gripper with independently actuated soft fingers, equipped with flex sensors and a camera, uses a reinforcement learning model to adapt its configuration based on real-time image and sensor data for optimal grasping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional robotic grippers are designed for specific object types, then grasping precision for those objects is improved, but adaptability to heterogeneous objects deteriorates
Solution Approach 1:
The gripper employs soft fingers with variable stiffness characteristics that can dynamically adapt to different object geometries and compliance levels. The soft material allows continuous adjustment of contact forces and finger configurations, enabling the same gripper structure to effectively grasp diverse objects from rigid to compliant types without mechanical reconfiguration
Solution Approach 2:
The system changes physical parameters of the gripper by utilizing the elastic deformation properties of soft materials. By controlling the degree of finger bending and contact pressure through actuation, the gripper adapts its grasping parameters to match different object characteristics, achieving both precision and versatility
2Measurement precision
If multiple specialized grippers are maintained for different object classes, then grasping performance for each class is improved, but system complexity and maintenance requirements worsen
Solution Approach 1:
The gripper design achieves multi-functionality through soft compliant fingers that can adapt to various object types including rigid, compliant, and fragile objects. The universal design eliminates the need for multiple specialized grippers by incorporating sensors and control algorithms that enable the same physical structure to perform diverse grasping tasks effectively
3Ease of operation
If rigid grippers are used for precise manipulation, then control precision is improved, but ability to handle fragile and compliant objects deteriorates
Solution Approach 1:
The gripper uses soft compliant fingers made from flexible materials that can conform to the shape of fragile and compliant objects. This flexibility allows the gripper to distribute contact forces evenly, preventing damage to delicate objects while maintaining precise control through sensor feedback and adaptive actuation
Data Source
AI summary
The present disclosure provides a vision based control of a reconfigurable soft robotic gripper. Conventional methods lack an intelligent control method which automatically adapts the configuration of the gripper based on the target object. The present disclosure includes a robotic gripper with a rigid palm and three soft fingers attached to the palm. Each finger is separately actuated using three separate motors. Out of the three fingers, one is fixed, and other two can move relative to the base, the motion of the movable fingers is actuated by motor(s). Each finger has multiple sensors to detect the magnitude of bending. A camera is attached to the base of the gripper, facing the object to be grasped. The camera image and the sensors measurements are given to a control unit and the control unit in turn gives the control signal to the actuator motors to suit the object to be grasped.