Abstract-We consider the task of grasping novel objects and cleaning fairly cluttered tables with many novel objects. Recent successful approaches employ machine learning algorithms to identify points on the scene that the robot should grasp. In this paper, we show that the task can be significantly simplified by using segmentation, especially with depth information. A supervised localization method is employed to select graspable segments. We also propose a shape completion and grasp planner method which takes partial 3D information and plans the most stable grasping strategy. Extensive experiments on our robot demonstrate the effectiveness of our approach.

Abstract-In this paper, we present a novel grasp selection algorithm to enable a robot with a two-fingered end-effector to autonomously grasp unknown objects. Our approach requires as input only the raw depth data obtained from a single frame of a 3D sensor. Additionally, our approach uses no explicit models of the objects and does not require a training phase. We use the grasping capability to demonstrate the application of a robot as an autonomous checkout clerk. To perform this task, the robot must identify how to grasp an object, locate the barcode on the object, and read the numeric code.We evaluate our grasping algorithm in experiments where the robot was required to autonomously grasp unknown objects. The robot achieved a success of 91.6% in grasping novel objects. We performed two sets of experiments to evaluate the checkout robot application. In the first set, the objects were placed in many orientations in front of the robot one at a time. In the second set, the objects were placed several at a time with varying amounts of clutter. The robot was able to autonomously grasp and scan the objects in 49/50 of the single-object trials and 46/50 of the cluttered trials.

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The objective of this paper is to improve the dynamic response and reduction in sluggishness in neural generalized predictive control (NGPC) with a modified performance index. A comparative study has been made between NGPC and a modified NGPC. The simulation results show that there is further significant improvement in the dynamic response using the modified NGPC.