# Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics
## 3 Current Advances and Trends
### Object Handover  
There are many concrete applications, where a robot has proven to be useful in helping humans by handing over objects, such as short-cycle repetitive tasks [67] or dynamic object handover tasks [68; 69]. In the last decade, some studies described the process of object handover between humans with the purpose of transferring that same execution to robots [70; 71]. However, that idealization of disassembling the handover process into different parts, giving separated instructions, has been discussed in a way to consider the handover as a single process [72]. There are some issues regarding the topic of object transfer between humans and robots. Figure 6: Scheme of the different layers of a generic human-robot interaction system. The uncertainties about the geometry and physical properties of objects emerge as an adversity for the robot to understand how it should grab the object. To overcome this concern, object pose estimation [73], grasp adaptation strategies [61] and tactile feedback systems [74] were developed. Nevertheless, for optimal object grasping, the robot should detect the shape, orientation, and possibly the mass center of each object. This detection must ensure a correct grasp for both static objects (robot as a giver) and in human hand objects (robot as a receiver). From the point of view of robot-to-human handover, an evaluation of proper object poses is discussed in [75]. Apart from the object itself, the point where the handover procedure will happen must be estimated; to predict this object transfer point, several studies on this theme have already been carried out [76; 77; 78]. Nonetheless, the proposed approaches of those works have some limitations: some studies only consider the robot as a receiver, others just as a giver. To tackle this issue, as an example, when the robot plays the giver role, it should estimate, through the human body dimension, position, and orientation, the best spatial point to deliver the object. This estimation could be successfully achieved by the adaptation of the optimization works that were already developed regarding this concern. Since a natural object transfer will rarely occur statically, the trajectory planning for giving or receiving an object must be continuously evaluated and planned [79]. For the robot to receive a continuously moving object (in the human hand), the trajectory to reach that object must be re-planned accordingly. To achieve a natural object transfer, the robot has to understand human intentions, by communication strategies apart from the physical contact. Human eye gaze cues are considered important to be detected and interpreted by the machine [80; 81]. Human-Robot Collaboration future development aims to integrate robots in human teamwork, ensuring the continuity of a fluent workflow. This means that the robot should give and receive the objects in a similar way as humans do. The human-like motion will result in a more comfortable collaboration with robots [82; 83], through the robot speed and reaction adaptability [84; 85]. Moreover, non-verbal communication could be used through physical properties for a human intention understanding [86]. Some other studies have taken human safety into a big consideration, developing grasping selection and reaction systems that avoid the collision with the human hand [87; 88; 89]. Focusing on the ultimate moment of any object handover procedure, when both agents are in contact with the object, the coordination of the object weight transfer should be ensured. This stands as the critical instant where the giver should make sure that the object will not fall [90; 91; 92]. Furthermore, for a dynamic handover, the giver should also be prepared for a possible regret from the receiver to take the object possession. At this point there is no giver or receiver agents, since, when both of them are in contact with the object, the human operator could want to get the object for himself or let it to the machine, despite the initial object possession.