Joint trainer and trainee haptic simulation (for learning by doing)

Introduction

For surgical gestures that are more difficult to acquire, the classic training method, in the field (in the operating room), consists, for a trainee, in operating on a patient, the hands guided by those of a trainer (nicknamed “four-handed” method). However, this does not currently find its equivalent in computer based simulators where the trainees are alone with their tools immersed in their environment.

It presents however some disadvantages: in particular, it is difficult for the two people to dose, for one and to estimate
for the other, the efforts to be made when the four hands are joined two by two because the effort is shared in such a random way
between the two people. It is a real obstacle for training the gesture because this dimension is distorted.

In the synthesis [Coles 2010] concerning educational simulators in the medical field, it appears that the current simulators are mainly based on real or virtual environments where the trainee is alone, which makes any possibility of guiding him in his actions difficult. Yet, as in practical training in four hands, especially for complex gestures, it is important that the trainer can intervene; to guide the trainees, to evaluate them immediately, or to correct potentially dangerous trajectories.

It is also necessary, for more flexibility in the training, to keep the possibility for the trainer to intervene in the simulation as he classically intervenes in classical practical training. It is not possible to program all scenarios in advance in the simulator. In use, the most recurrent can gradually be integrated into the simulator, but there will always be special cases where the intervention
of the trainer will be necessary: ​​to unblock the trainees, to advise them, ... Hence the interest of proposing simulators integrating the trainer into the simulation.

The da Vinci Si dual-console system robot [g71] offers a training mode for two concurrent users. However, only one user at a time has access to the instruments and neither user has no haptic feedback.

In dual user systems, several haptic interfaces are connected to a robot (real or virtual) thanks to a software. The parameter α determines the dominance of each user over the slave. When α = 1 (resp. α = 0, it is user 1 (resp. 2) who has complete control of the slave. When 0

Contributions

First, we designed the bases of a new educational simulator, gesture training, usable to two users (trainer and learner) based on a novel controller, managing energy exchanges between sub-systems (Energy Shared Control - ESC) [Liu 2015].The energy approach (modeling by Hamiltonian ports) offers the advantage of proving intrinsically that the system is passive whatever the evolution of α (which is not the case time-invariant linear dual-user models where α is a parameter and is therefore supposed to be constant).
Whatever the level of authority granted to a user, the latter perceives an effort feedback in accordance with the interaction efforts tool-environment, even if it is not the user at the origin of this interaction; thus the person who observes the movement feels the same efforts as the person actually handling the tool. This property was not seen ever in the scientific literature.

We validated it experimentally using axis 1 (vertical) of two Omni haptic interfaces and one virtual interface (simulated under Matlab) . Having noticed that the trainer needs to regain control very quickly in the event of an erroneous or dangerous gesture (like the driving instructor who can brake on his own brake pedal), we have developed the AAA (Adaptive Authority Adjustment) function which, when in evaluation mode, switches control back (changes α) to the trainer as soon as the trajectory of its interface moves away (necessarily voluntarily) from that of the learner.

However, this solution had the disadvantage of requiring two parameters that were difficult to adjust by a non-professional trainer.
We compared the performance of ESC against two recognized architectures offered by Khademian and Hashtrudi-Zaad [Khademian 2011](Complementary Linear Combination (CLC) and Masters Correspondence
with Environment Transfer (MCET)), in simulation [Liu 2016]. This study demonstrated that the performance of ESC in terms of position tracking were equivalent to those of CLC and MCET. However, the force feedback from ESC is intrinsically better for educational applications because CLC and MCET do not allow to realize demonstrations and evaluations involving simultaneous positioning and force feedback to both users.
We then improved ESC for which the environment and users were assumed to be passive (which is debatable particularly concerning the users). We added a passivity controller (Time Domain Passivity Controller: TDPC) to keep the system passive whatever the behavior of the slave environment and of the users and independently of α and the parameters of the IPC controllers. [Liu 2016]

At the end of Fei Liu's Ph.D., this simulator had only one degree of freedom (one rotation).
Angel Licona's objectives were to extend this simulator in terms of degrees of freedom.

Thus, we tested this architecture with n degrees of freedom by duplicating ESC for each joint. This supposes that the three interfaces have the same kinematics. That is the case for the masters but one can argue for the slave. We experimentally tested this approach with three degrees of freedom. The results are available in [Liu 2019].
We also proposed a new algorithm for AAA (also extended to n degrees of freedom) which now requires only one easily adjustable parameter in continuous by the trainer, in order to leave more or less freedom of movement to the learner.
Experiments were carried out integrating all these developments . They were published in [Liu 2019b].

We have studied the extension of this architecture to m > 2 users in order to meet the needs of collective training during which, for example, the trainer would only have to perform a single demonstration to m − 1 simultaneous learners. All other scenarios are possible as long as a single user is in control on the slave and the other observers. This experimentally validated study was published as part of the IROS 2019 conference [Licona 2019].

We have also studied the use of ESC with haptic interfaces with different kinematics to be able to control a slave robot different from the haptic interfaces, which seems the most interesting configuration in practice. For this, we proposed to use ESC for each dimension in Cartesian space instead of the joint space, hypothesizing that the couplings between these dimensions would be considered as disturbances by each IPC controller and absorbed as such.