# A Human-Inspired Control Strategy for Improving Seamless Robot-To-Human Handovers
## 2 Design of the Robotic Human-Inspired Control Strategy for HRH
### Robotic Hybrid Position/Force Control Strategy for the HRH Tasks  
Robot force control is a fundamental requirement in the achievement of the control of the robot's real-time path in any physical HRI task. It has been developed in the past three decades, using for example force, torque and visual feedback to operate robots to suitably participate in unstructured environments. [PERSON] and [PERSON] [43] introduced a new method for robot force control based on two control loops, consisting of combined position and force control systems, namely hybrid position/force control. One of the crucial advantages of using the hybrid control is that the position and force information is analysed synchronously and independently. These two outputs are combined in the final stage before being converted to drive the robot actuators using joint torque control [44]. In this research, hybrid PID position/impedance control was implemented. This is due to the fact that PID position control is the most widely used and reliable method for controlling a robot manipulator position. Additionally, a method for the automatic tuning of PID controllers in a closed loop can be estimated using a transfer function model. However, the PID controller may not suitable for force control because the derivative term (\(K_{d}\)) is too sensitive to noise. This could induce a destabilizing impact on the robot force control system [45]. Interestingly, [PERSON] et al. [46] proposed the mathematical models of the human hand while interacting with a HHH task. The human applied force is formulated by the human arm impedance which is made up of mass, stiffness and damping factor,  
Figure 4: Reference frames of the HRH system. respectively. Consequently, to imitate the real-world human force dynamics, impedance control, which efficiently controls both the motion of the robot and its contact forces, was selected in the robotic force control loop. Figure 5 illustrates the hybrid PID position/impedance control scheme, which was designed based on the study by [PERSON] et al. [47]. It is made up of two control loops each of which has an individual information sensor system, i.e., (1) multi-axis force/torque sensor used to detect the force applied to the HSR robot end effector and (2) the rotary encoders used to measure the robot joint positions. \(X_{R}\) and \(F_{R}\) represent the references of the position and force control schemes, which can be generated using handover experimental results, as explained in Equations (1) and (2). The outcomes from the position (\(X_{P}\)) and force control (\(X_{F}\)) loops are fused together as a set of incremental displacements (\(X_{u}\)), namely, the hybrid position/force control, as exhibited in Equation (17). The parameters \(X_{E}\) and \(F_{E}\) are the errors of the position in Cartesian coordinate and force control algorithms, respectively. The matrix \(S\) represents the compliance selection matrix used to specify the number of DOF in the robotic control system, where \(A\) and \(B\) represent the robotic position and force controllers, respectively. \[X_{u}=X_{P}+X_{F}=A[(S\times X_{E})]+B[((1-S)\times F_{e})] \tag{17}\]  
The positions of the robot in joint space (\(q_{u}\)) can be computed based on an inverse Jacobian matrix as expressed in the following equation. \[q_{u}=J(q)^{-1}X_{u} \tag{18}\]  
The position feedback of the robot in Cartesian space (\(X\)) is adopted the forward kinematic function based on the position feedback of the robot joint space detected by the encoders (\(q_{s}\)) as formulated in Equation (19). \[X=f(q_{s}) \tag{19}\]  
According to the robot control design, a PID controller was implemented on the robot position control. An incremental discrete-time PID control algorithm with a sampling period (\(\tau\)) and the discrete-time interval \(k\) was implemented.