Abstract
Mobile manipulators are widely used in different fields for transferring and grasping tasks such as in medical assisting devices, industrial production, and hotel services. It is challenging to improve navigation accuracies and grasping success rates in complex environments. In this paper, we develop a multisensor-based mobile grasping system which is configured with a vision system and a novel gripper set in an UR5 manipulator. Additionally, an error term of a cost function based on DWA (dynamic window approach) is proposed to improve the navigation performance of the mobile platform through visual guidance. In the process of mobile grasping, the size and position of the object can be identified by a visual recognition algorithm, and then the finger space and chassis position can be automatically adjusted; thus, the object can be grasped by the UR5 manipulator and gripper. To demonstrate the proposed methods, comparison experiments are also conducted using our developed mobile grasping system. According to the analysis of the experimental results, the motion accuracy of the mobile chassis has been improved significantly, satisfying the requirements of navigation and grasping success rates, as well as achieving a high performance over a wide grasping size range from 1.7 mm to 200 mm.
Highlights
Mobile manipulators are widely used in different fields for transferring and grasping tasks such as in medical assisting devices, industrial production, and hotel services
In the process of mobile grasping, the size and position of the object can be identified by a visual recognition algorithm, and the finger space and chassis position can be automatically adjusted; the object can be grasped by the UR5 manipulator and gripper
In order to ensure that the mobile robot runs as close to the global path as possible, an error term of cost function based on DWA is proposed and a comparative trial is carried out between our method and DWA running on ROS [25]. e mobile grasping robotic system designed in this paper uses a combination of the soft gripper, the UR5 manipulator, and the mobile chassis to successfully complete the grasping task
Summary
E stepping motor rotates forward or reverses according to the command At this time, the fingers fixed on the stepper motor remain motionless. E finger fixed on the slider moves away from or near the stepping motor and moves to the designated position according to the number of pulses calculated by the single-chip microcomputer to realize the grasping of objects of different sizes. In this paper, according to grabbing habits of individuals, we propose a kind of soft gripper that can simulate human hand grabbing If this kind of gripper can grab many kinds of goods in daily life, it will be very helpful for grasping robots. The sliding of the slider can change the size of the grasping space, and the linear motor of different lengths can be selected according to the different objects to be grasped. Combined with the advantages of the variable grasping space of the slide, the strategy of grasping objects of various sizes is realized
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