# A Human-Inspired Control Strategy for Improving Seamless Robot-To-Human Handovers
## 1 Introduction  
Recently, robots have been widely developed over the last decades to meet the requirements of improving human-robot interaction (HRI). HRI is a field of study to understand, design and evaluate robotic systems, while interacting with humans [1]. The interaction involves several communication forms and can be mainly categorized into two types: remote interaction (i.e., search and rescue [2, 3, 4], military and police [5, 6], space exploration [7, 8, 9], etc.) and proximate interaction (i.e., assistive robotics and educational robotics [10, 11, 12, 13, 14], home or industry [15, 16], etc.). In this research, the field of social robotics and human-robot interaction are highlighted, in which robots are being developed to serve in human assistive capacities. One of the main challenges in close proximity interaction is to efficiently establish a framework for seamless human-robot handovers (HRI). This will allow a human to act jointly with a robot safely and reliably. The researchers [17] claimed that understanding of behavioural control strategies of human-human interaction (HHI) is fundamental to design an effective HRI system. In addition, [PERSON] et al. [18] also addressed that understanding the principle of human haptic interaction, when two humans work together in a joint effort to complete a shared task, is crucial in designing an effective HRI system. This section emphasizes the background of handover-based research, since human-human handovers (HHH) are the ultimate benchmark for seamless handovers. A quiver is defined as an agent who holds an object and passes it to another. In the physical interaction, a receiver is a particular position that receives the object by starting pulling it. Afterwards,the receiver takes responsibility for the object throughout the transferring process [19; 20]. Much of the relevant HHI research, which has steadily increased to enhance the understanding of HHI behaviour, has been reviewed. Previous studies have examined issues regarding investigating the control characteristics of two humans in a physical handover task, for examples, analysing (1) the influence of velocity [21; 22] and trajectory [23; 24] on the handover movements, (2) grip forces and load forces in the object exchange [25], (3) grasp points [26; 27] and locations [28; 29] and finally, (4) configuration [30; 31] of the exchanged object. These can be used as conceptual frameworks for designing control systems for cooperative robots to work with other partners by imitating human-based behaviour control strategies. [PERSON] et al. [32] investigated the human behavioural responses in HHH tasks under various conditions. The paradigm findings show human dynamic characteristics, i.e., interactive force analysis, suitable transfer locations between the givers and receivers and the handover sequences. The handover is distinctively categorized into sending-transferring-receiving phases, where the giver agent primarily decides to release the object. This will be useful for developing a robotic behaviour-based approach in seamless HRH in future. [PERSON] et.al [33] analysed how humans (givers and receivers) determine the locations of object transfer during handovers for a good understanding of the mechanisms of human social behaviour. The study also presented a linear model with the influential factors affecting the handover locations. It consists of participant heights, genders and social dominance of the two partners and the distance between both humans. [PERSON] et al. [34] proposed adaptive coordination strategies for physical HRH. It was based on the identification of HHH strategies regarding how people adapt their handover actions to the workload of their partners. The newly developed approach involving two baselines, namely, (1) proactive and (2) reactive coordination techniques, enabled similarly fluid and effective HRH tasks. [PERSON] et al. [35] proposed a robotic navigation planner and a manipulation planning framework by first understanding the human dynamic characteristics of the haptic interaction.