# Direction-Based Hybrid Strategy Combining Pushing and Hitting for Fast Object Singulation
## 1 Introduction  
Humans pick and place things easily because humans are blessed with a brain that instantly finds out ways to complete the task. However, for robots, even the simple task is much more difficult and complex. There are two different ways to move an object from the initial position to the goal position by using a robot manipulator; prehensile and non-prehensile methods. In prehensile manipulation, the robot grasps the object and moves it to the target position. However, in non-prehensile manipulation, the robot moves the object to the target position by pushing and hitting. A combination of both techniques not only provides the desired object singulation but also consumes less time. Manipulation methods can be divided into two types: quasi-static manipulation and dynamic manipulation. In the case of quasi-static manipulation, there is always contact between the manipulator and the object even after collision. Alternatively, in the case of dynamic manipulation, the object may lose its contact with the manipulator after collision. Approaches related to robotic pushing have been extensively studied [1, 2]. However, these approaches consume a lot of time since the pushing-only approach is helpful only for a few objects. In the case of multiple objects, this technique is not suitable. [PERSON] et al. [3] proposed a planning framework based on pushing in order to singulate an object in clutter. Although this approach helps in grasping objects that are ungraspable otherwise, the problem with this technique is the unnecessary pushing actions that result in the unnecessary displacement of objects. As robots have already made their way into the daily lives of humans, they tend to perform things that are easy for humans. Pushing is one of the approaches utilized daily by humans in order to manipulate or grasp different objects. [PERSON] et al. [4] provided a literature review related to robotic pushing, where he has divided pushing into six major categories: (i) pure analytical, (ii) hybrid, (iii) dynamic analysis, (iv) physics engines, (v) data-driven, and (vi) deep learning. In dynamic manipulation, the collision-based singulation approach is performed. [PERSON] et al. [5] suggested an approach that was based on hitting. They have used a virtual world simulator that relied on a dynamic model and have estimated all of the physical properties of objects in an environment. After successful hitting in a virtual world, real-world hitting is performed. Different studies have also discussed approaches related to impulse-based techniques between a robot and an environment [6; 7]. Moreover, it should be noted that, during the singulation by hitting, multiple impacts may occur simultaneously, and in that case, its analysis involves issues that cannot be solved by the simple extension of two-body impact, as discussed, for example, by [PERSON] [8]. [PERSON] et al. [9] and [PERSON] et al. [10] discussed the criterion that must be satisfied by the solution for simultaneous impacts and proposed methods for analyzing simultaneous impacts. These methods are focused on the analysis of the impact. This paper has two contributions. First, we have proposed a hybrid approach that uses both pushing and hitting for the singulation of objects in clutter. Combining the advantages of pushing and hitting would be helpful in the singulation of objects in clutter. Second, we have also introduced the desired direction of hitting and pushing to facilitate the singulation of objects. Our approach based on the above contributes results in the fast singulation of objects in clutter. This paper proposes a blend of these two approaches in scenarios where only one approach alone cannot be effective in order to singulate objects. Section 2 discusses the motivation of this study. The hitting approach is introduced in Section 3. Sections 4 and 5 deal with a parameter estimation for a virtual world simulation and experimental verification. Section 6 deals with comparative analysis.