## 2 Related Work  
The optimization of operations inside a warehouse is currently characterized by several research areas. In particular, the implementation of a robotic system able to assist human workers in their tasks requires the capability to effectively plan and optimize the sequence of actions [2; 3; 4], to correctly localize persons and objects [5] and to interact with the environment and other systems in the network [6]. Since the advent of Industry 4.0, the requirements of optimizing the transport and distribution of products has encouraged the use of autonomous guided vehicles within modern automated warehouses [7]. Moreover, autonomous mobile robots have been introduced to improve flexibility and robustness in modern industrial contexts [8]. Nowadays, the potential collaboration between cobots and mobile platforms has received increasing efforts from industrial and scientific research, particularly for logistic applications [9]. [PERSON] et al. [10] explored the possibility of employing a mobile collaborative system for palletizing operations. The hardware consists of a lifting device equipped with a pneumatic gripper, a powered conveyor and a set of sensors which allows interaction between the system itself and the environment. Vacuum grippers are usually adopted for depalletizing cardboard boxes [11; 12; 13]. However, this solution is not generally safe, since cardboard boxes cannot always hold the weight of the items that they contain. [PERSON] et al. [13] designed a depalletizing system where a second robot arm is used to support the boxes during motion. A robot manipulation system based on 3D vision and a vacuum gripper, for the detection and unloading of cardboard boxes from shipping containers or semi-truck trailers, is presented in [11]. A fixed-base robot depalletizing system designed for supermarket logistic processes is described in [12]. Similarly,the application of vacuum technology was proposed in [13; 14], whereas [PERSON] et al. [15] developed a mobile robot equipped with a self-weight compensation system. However, these solutions may lack flexibility, and vacuum gripping solutions may be hard to implement on AMRs, especially small-sized ones. In contrast, with previous systems, a non-prehensile approach of manipulation was suggested by [PERSON] et al. [16], where items are dragged aboard the mobile robotized system. Non-prehensile manipulation strategies are a subject of growing interest, both in the research and industrial fields, because with the reduction in the overall weight supported by the gripper, the minimization of the risk of falls and the capability to perform specific motions in a cluttered environment would be impossible under normal grasping scenarios. In [17], a new planning framework to exploit the funneling effect of pushing to deal with uncertain and clutter environments is proposed. Similarly, in [18] a framework that takes into account the human presence in cluttered environments is analyzed. [PERSON] et al. [19] presented a motion planning analysis for the optimization of the stability and control of an asymmetric object during non-prehensile manipulation. [PERSON] et Al. [20] proposed a quasi-static analysis to define a dynamical system to predict the object behavior in function of friction forces. In the industrial scenario [21], the manipulation of a flexible belt exploiting the friction between the belt and the gripper is discussed. Our work aimed to promoting new studies on the interaction forces between the object to be picked and the support layer to further simplify the depalletizing operation in a shared human-robot environment. In terms of perception, similarly to what is proposed in this paper, [PERSON] et al. [22] presented a genetic algorithm to recognize loads on a pallet.