An Integrated Multi-Sensor Network for Adaptive Grasping of Fragile Fruits: Design and Feasibility Tests

Abstract

Secure grasping of fragile fruits and other agricultural products without potential slip and damage is still a challenge due to the size and shape varying, bruise susceptible, as well as hardness changing during fruit and vegetable maturation. In the robotic grasping process, the mechanical damage mainly depends upon the aggressiveness of the gripper and the sensitivity of the product to the damage. In this study, a flexible gripper integrated with multi-sensor network is designed and tested. The network proposed includes three kinds of sensors that enable the gripper to grasp various products with the sense of touch and visual perception. Particular attention has been attached to the sensors applied between the fingers, and this makes sensing and grasping capabilities improved. To create an accurate grasping system, a grasping algorithm and the force control model are proposed for any bending state based on Cosserat theory. The boundary detection is included in the grasping algorithm, detecting the shape edge by some certain point calculation. The created grasping system guarantees mechanical compliance by evaluating and adjusting the finger status including force, angle, and direction. Multi-group tests have been done on grasping several objects of different sizes and materials in daily life. The relationship between force, bending, and surface material is also analyzed and compared under different conditions. The numerical comparisons related to the measurement error are analyzed based on their standard deviations. Experimental results indicate that this flexible manipulator with proposed system and strategy has better grasping ability for fragile fruits with its good flexibility and dexterity.

Human Grasp Mechanism Understanding, Human-Inspired Grasp Control and Robotic Grasping Planning for Agricultural Robots

“…In many agricultural tasks, potential slippage and damage risks should be avoided when grabbing and placing objects due to the large differences in shape, hardness, and surface properties of agricultural products [ 12 , 13 ]. Thus, the proper grasping configuration (that is, the gripping posture of the hand relative to the object) is necessary for the grasping of the manipulator.…”

Fruit Classification Utilizing a Robotic Gripper with Integrated Sensors and Adaptive Grasping

“…e gripper is a core component of a robot. It serves as the end-effector of the mechanical arm and performs tactile information perception and haptic data collection [2,3]. e gripper plays a crucial role in many manipulation tasks.…”