# Review of Advanced Medical Telerobots
## 2 Medical Telerobotic Topologies
### Multilateral Teleoperation
It should also be noted that during a motor training scenario, the motion of the skilled user (such as the surgical trainer) has been seen as a reference for evaluating the performance of the second user, taking advantage of the multi-user design [216; 217]. Besides, the expert trajectory has been used to generate a guiding force field at the trainee's robot so that the trainee can develop the needed spatial and visuospatial mapping based on the kinesthetic guidance from the expert side. This is called robot-mediated hand-over-hand training [206; 208; 258; 278]. Another use of this topology is to enhance the operability of the task-side (follower) robotic system when there exists kinematic and structural asymmetry, causing discrepancies between degrees of freedom of leader and follower robots. In this scenario, each user may take control of parts of the follower robotic system hence increasing the human interface dexterity [279; 280; 281; 282]. As another application, surgical tasks such as needle insertion can benefit from this topology. For this, the needle insertion can be divided into two independent tasks of (1) controlling the position and orientation of the needle, and (2) controlling the depth of insertion [230]. Yet another example of such a scenario is therapist-in-the-loop (TIL) mirror robotic rehabilitation for post-stroke patients, using which the therapist's trajectories (first leader robot) is modulated by the user's hand on the less affected side in a mirrored fashion (second leader robot) to rehabilitate the hand on the affected side (the follower robot). This architecture not only allows for higher safety and reliability of the therapy but can potentially allow for stimulating neural recovery through the medium of mirror rehabilitation [247; 253; 254]. Motivated by the significant benefits of ML/SF topology in several real-life applications, a variant of this topology is also investigated in the literature when the interaction between the follower robot and the environment is virtualized so that multiple users at multiple leader sides can share the control of a certain task in a virtual reality environment [250; 255; 256; 283; 284; 285; 286]. The aforementioned application grants significant benefits for the simulation-based medical applications such as surgical training [287], and non-medical applications such as collaborative sculpting and even online computer gaming [250; 255; 256]. For virtualized ML/SF topology, the virtual reality environment can be shared in a single server (client-server) format or distributed among users (peer-to-peer) [283]. Despite several benefits, there are some existing challenges with the use of this topology. It should be noted that in both virtualized and real-world usages of the ML/SF topology, a question is the fusion methodology between the commands of different users and the corresponding synchrony [218; 284]. It should also be noted that such topology may suffer from a nonhomogeneous distribution of delay between different operators and between them and the follower robot, which calls for a specialized stabilization framework. One of the major challenges with the distributed delay is the complexity of the stabilization architecture [4; 218; 272; 273]. Improving the performance, stability, and functionality of ML/SF topology is ongoing research, and several advanced topics have been investigated during the last decade. Examples are wave-variable controller [284], graph theory, and network topology optimization [256], feedback-based synchronization controller consisting of a linear compensator with a Smith predictor [288], virtual coupling scheme [285, 289], event ordering via global time coordinate frame [290] and remote dynamic proxies [291, 292, 293, 294, 295].