**5. QoS control**

QoS control is effective for solving the problems occurred by network delay, delay jitter, and packet loss. As described in the previous section, in the remote robot operation, there exists a control loop between a haptic interface device and a robot. We need to carry out QoS control in the loop to improve the QoE. This means that we need to carry out QoS control at a haptic interface device terminal and/or at a robot terminal. There are many types of QoS control such as traffic management and control, error control, spatiotemporal synchronization control (we can carry out media synchronization control or causality control to achieve spatiotemporal synchronization), consistency control, adaptive reaction force control [4], and position control using force information [17]. We also introduce serval types of QoS control which we previously proposed for the remote robot operation.

## **5.1 Media synchronization control**

Media synchronization control is used to solve the problems occurred by network delays and delay jitter. The control can be grouped into intra-stream synchronization control, inter-stream synchronization control, and inter-destination (or group) synchronization control [18].

Intra-stream synchronization control is used to preserve the timing relation between media units (MUs, which are information units for media synchronization) [19] in a single media stream. There are several types of intra-stream synchronization control, for example, Skipping [19], Virtual-Time Rendering (VTR) [19], and so on. Skipping outputs MUs on receiving the MUs, and when the sequence number of a received MU is smaller than that of the last-output MU, the control discards the received MU. VTR has a virtual-time axis which can be contracted or expanded dynamically according to the network delay, and MUs are output along the virtual-time axis.

In multimedia applications, if we only carry out intra-stream synchronization control for each media stream separately, the temporal relationship among media streams may be disturbed and QoE may be deteriorated. In order to solve the problem, we need to carry out inter-stream synchronization control. The VTR can be used for intra-stream and inter-stream synchronization control. Under the control, one media stream is handled as the master stream and the others are dealt with as slave streams. VTR carries out only the intra-stream synchronization control for the master stream, and it exerts the inter-stream synchronization control after carrying out the inter-stream synchronization control for the slave streams.

In remote cooperation, in order to improve the efficiency of cooperative work, it is important to output MUs simultaneously at different terminals. Group (or inter-destination) synchronization control outputs each MU simultaneously at different terminals. We proposed three schemes for inter-destination synchronization control (i.e., the master–slave destination scheme, synchronization maestro scheme, and distributed control scheme) [4].

**63**

force is reduced.

of the control by experiment.

*QoS Control in Remote Robot Operation with Force Feedback*

Causality control keeps the causal (i.e., temporal order) relationships among events. Here we introduce two typical examples of causality control; one is the Δ-causality control [20], and the other is the adaptive Δ-causality control [21].

In the Δ-causality control, each MU has a time limit which is equal to the generation time of the MU plus Δ seconds for preservation of the real-time property. The control output the MU at the time limit, and if the MU is received after the time limit, it is discarded because it is considered useless. The adaptive Δ-causality control dynamically changes the value of Δ according to the network load. The control does not discard an MU received after the time limit and uses the MU for prediction.

As the network delay increases, the reaction force applied to a haptic interface device becomes larger and the output quality of haptic media becomes deteriorated. The adaptive reaction force control [4] can be used to solve the problem. We calculate the reaction force based on the spring-damper model [22] or depending on the force sensed by the force sensor. In the spring-damper model, the reaction force consists of the elasticity and viscosity. The elasticity is force exerted by deformation of a spring or rubber, for example. When a spring is pushed or pulled. The elasticity is proportional to the depth of a spring when the spring is pushed, and it is calculated by multiplying the depth by the elastic coefficient. The viscosity is force or resistance exerted by fluids, for example, when we move an object through the fluids (e.g., water and oil). The viscosity is proportional to the relative velocity (i.e., the velocity of the object relative to the fluids), and it can be calculated by multiplying the relative velocity by the viscosity coefficient. The adaptive reaction force control includes the adaptive viscosity control [23], adaptive elastic control [24], and adaptive viscoelasticity control [25]. The adaptive elastic control dynamically changes the elastic coefficient according to network delay, the adaptive viscosity control dynamic changes the viscosity coefficient according to the network delay and the velocity of the haptic interface device,

and the adaptive viscoelasticity control combines the two types of control.

In order to reduce the force applied to an object operated in cooperative work between the remote robot systems with force feedback, the robot position control with using force information is proposed [17]. The proposed control moves the robot by taking advantage of human perception of force direction by experiment. The control finely adjusts the robot position dynamically in the direction where the

Since the remote robot system with force feedback is delay sensitive [26], we apply Skipping to the system at both master and salve terminals. This means that Skipping is applied to the operation with a single remote robot system and that between the two remote robot systems. For the operation between the two remote robot systems, we apply the adaptive reaction force control, adaptive Δ-causality control, and position control using force information for the remote cooperation between two remote robot systems with force feedback. That is, we apply the control for the cooperation between users (i.e., each user operates a haptic interface device to control a remote robot to do collaborative work), and for the cooperation between the user and robot. We also applied the position control using force information for the cooperation between the two robots. We also investigate the effects

**5.4 Position control using force information**

*DOI: http://dx.doi.org/10.5772/intechopen.97011*

**5.3 Adaptive reaction force control**

**5.2 Causality control**
