Dr Sajeeva Abeywardena

Robot Assisted Surgery is attracting increasing amount of attention as it offers numerous benefits to patients as well as surgeons. Heart surgery requires a high level of precision and dexterity, in contrast to other surgical specialties. Robot assisted heart surgery is not as widely performed due to numerous reasons including a lack of appropriate and intuitive surgical interfaces to control minimally invasive surgical tools. In this paper, finger motion of the surgeon is analyzed during cardiac surgery tasks on an ex-vivo animal model with the purpose of designing a more intuitive master console. First, a custom finger tracking system is developed using IMU sensors, which is lightweight and comfortable enough to allow free movement of the surgeon's fingers/hands while using instruments. The proposed system tracks finger joint angles and fingertip positions for three involved fingers (thumb, index, middle). Accuracy of the IMU sensors has been evaluated using an optical tracking system (Polaris, NDI). Finger motion of the cardiac surgeon while using a Castroviejo instrument is studied in suturing and knotting scenarios. The results show that PIP and MCP joints have larger Range Of Motion (ROM), and faster rate of change compared to other finger/thumb joints, while thumb has the largest Fingertip WorkSpace (FWS) of all three digits.

A novel master controller for robot-assisted minimally invasive surgery (RAMIS) is introduced and used to control a da Vinci EndoWrist instrument. The geometric model of the master mechanism and its mapping to the geometry of the EndoWrist tool are derived. Experimental results are conducted to open and close the jaws of an EndoWrist tool, and show that the developed mapping algorithm is accurate with a root mean square error of 0.7463 mm.

Humans are intrinsically unstable in quiet stance from a rigid body system viewpoint; however, they maintain balance thanks to neuro-muscular sensory properties whilst still exhibiting postural sway characteristics. This work intro-duces a one-degree-of-freedom supernumerary tail for balance augmentation in the sagittal plane to negate anterior-posterior postural sway. Simulations showed that the tail could success-fully balance a human with impaired ankle stiffness and neural control. Insights into tail design and control were made; namely, to minimise muscular load the tail must have a significant component in the direction of the muscle, mounting location of the tail is significant in maximising inertial properties for balance augmentation and that adaptive control of the tail will be best suited for different loads held by a wearer.

A desktop haptic device is used to teleoperate an industrial redundant and compliant robotic arm with a surgical instrument mounted on its end-effector. The master and slave devices are coupled in a bilateral position-position architecture. Force feedback is provided by the master haptic device to the user, from the position of the slave's wrist. A surgical task (palpation) that involves force feedback is presented and tested in a user study with surgeons and non-medical participants. Results show that users easily discern between three different materials during palpation given minimal familiarisation time. Active constraint enforcement is also integrated with the system as a sensitive area around the palpation samples which the slave instrument is prohibited to enter.

Humans are intrinsically unstable in quiet stance from a rigid body system viewpoint; however, they maintain balance, thanks to neuro-muscular sensory control properties. With increasing levels of balance related incidents in industrial and ageing populations globally each year, the development of assistive mechanisms to augment human balance is paramount. This work investigates the mechanical characteristics of kinematically dissimilar one and two degrees-of-freedom (DoF) supernumerary robotic tails for balance augmentation. Through dynamic simulations and manipulability assessments, the importance of variable coupling inertia in creating a sufficient reaction torque is highlighted. It is shown that two-DoF tails with solely revolute joints are best suited to address the balance augmentation issue. Within the two-DoF options, the characteristics of open versus closed loop tails are investigated, with the ultimate design selection requiring trade-offs between environmental workspace, biomechanical factors, and manufacturing ease to be made.

A new six-dof epicyclic-parallel manipulator with all actuators allocated on the ground is introduced. It is shown that the system has a considerably simple kinematics relationship, with the complete direct and inverse kinematics analysis provided. Further, the first and second links of each leg can be driven independently by two motors. The serial and parallel singularities of the system are determined, with an interesting feature of the system being that the parallel singularity is independent of the position of the end-effector. The workspace of the manipulator is also analyzed with future applications in haptics in mind. [DOI: 10.1115/1.4007489]

The Monash Epicyclic Parallel Manipulator (MEPaM) is a three-legged six-degrees-of-freedom (dof) parallel mechanism with base mounted actuators. Due to the architecture of MEPaM, a closed form solution to the direct geometric problem was obtained. The concepts of Z-Width and transparency were used to analyze the performance of MEPaM as a haptic device. It was found that the Z-Width is superior to two out of three commercially available six-dof haptic devices. Closed-loop control was found to provide the most transparent interaction.

The Monash Epicyclic Parallel Manipulator (MEPaM) is a novel six-degree-offreedom (dof) parallel mechanism with base mounted actuators. Closed form equations of the inverse dynamic model of MEPaM are obtained through two different methods, with simulation showing these models to be equivalent. The base inertial parameters for the dynamic model of MEPaM are determined, reducing the number of inertial parameters from 100 to 28. This significantly simplifies the dynamic calibration model and thus the number of computations required.

A new algorithm is proposed to estimate the tool-tissue force interaction in robot-assisted minimally invasive surgery which does not require the use of external force sensing. The proposed method utilizes the current of the motors of the surgical instrument and neural network methods to estimate the force interaction. Offline and online testing is conducted to assess the feasibility of the developed algorithm. Results showed that the developed method has promise in allowing online estimation of tool-tissue force and could thus enable haptic feedback in robotic surgery to be provided.

Neural control is paramount in maintaining upright stance of a human; however, the associated time delay affects stability. In the design and control of wearable robots to augment human stance, the neural delay dynamics are often overly simplified or ignored leading to over specified systems. In this letter, the neural delay dynamics of human stance are modelled and embedded in the control of a supernumerary robotic tail to augment human balance. The actuation, geometric and inertial parameters of the tail are examined. Through simulations it was shown that by incorporating the delay dynamics, the tail specification can be greatly reduced. Further, it is shown that robustness of stance is significantly enhanced with a supernumerary tail and that there is positive impact on muscle fatigue.