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Cooperative Control of Bimanual Continuum Robots for Automated Knot-Tying in Robot-Assisted Surgical Suturing Quaicoe, Enoch; Nada, Ayman; Ishii, Hiroyuki; El-Hussieny, Haitham
Journal of Robotics and Control (JRC) Vol 5, No 4 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i4.21617

Knot-tying, a crucial yet intricate surgical task, remains a challenge in Robot-assisted Minimally Invasive Surgery (RAMIS) performed under teleoperation. While existing studies on automated knot-tying mostly focus on rigid-link robots, whose dexterity, adaptability, and inherent safety in RAMIS are outperformed by continuum robots, this research takes a novel approach by developing a unique cooperative control scheme for bimanual continuum robots, specifically designed for automated knot-tying tasks in RAMIS. We meticulously plan two effective knot-tying trajectory scenarios and develop the cooperative control scheme for the bimanual continuum robots, leveraging the well-known Jacobian transpose kinematic algorithms to ensure their precise and collaborative knot-tying trajectory tracking performance. The control scheme incorporates a switching mechanism to guarantee the robots’ collaboration and synchronous operation during the knot-tying trajectory tracking process. The effectiveness of our cooperative control scheme is illustrated through simulation studies using MATLAB/Simulink in terms of trajectory tracking performance. Meanwhile, ten Monte Carlo simulations are conducted to analyze the system’s robustness against pulse disturbances that could occur in surgical settings. All ten simulations returned similar error values despite the increasing disturbance levels applied. The results not only demonstrate the seamless collaboration and synchronous operation of the bimanual continuum robots in precisely tracking the pre-planned knot-tying trajectories with errors less than 0.0017 m but also highlight the stability, effective tuning and robustness of our cooperative control system against pulse disturbances. This study demonstrates precision, robustness, and autonomy in bimanual continuum robotic knottying in RAMIS, promising safe robot-patient interaction and reduced surgeon workload and surgery time.

Soft Tissue Compliance Detection in Minimally Invasive Surgery: Dynamic Measurement with Piezoelectric Sensor Based on Vibration Absorber Concept Hashem, Radwa; El-Hussieny, Haitham; Umezu, Shinjiro; El-Bab, Ahmed M. R. Fath
Journal of Robotics and Control (JRC) Vol 5, No 5 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i5.22895

Recent research in the medical field has increasingly focused on tissue repair, tumor detection, and associated therapeutic techniques. A significant challenge in Minimally Invasive Surgery (MIS) is the loss of direct tactile sensation by surgeons, as they cannot physically feel the organs they operate on. Tactile feedback enhances patient safety by tissue differentiation and reducing inadvertent damage risks. Addressing this challenge, this study introduces a novel tactile sensor designed for compliance detection to enhance tactile feedback in MIS. The sensor operates on a 2-Degree-of-Freedom (2-DOF) vibration absorber system, utilizing a piezoelectric actuator with a calibrated stiffness of 188 N/m. It interprets tissue stiffness regarding a spring constant, Ko, and measures changes in soft tissue stiffness by analyzing variations in the vibration absorber frequency, specifically at the frequency which causes the first mass to exhibit zero amplitude. The effectiveness of this sensor was evaluated through tests on polydimethylsiloxane (PDMS) specimens, which were engineered to replicate varying stiffness found in human organ tissues. Young's modulus of these specimens was determined using a universal testing machine, showing a range from 10.12 to 226.89 kPa. Additionally, the sensor was applied to measure the stiffness of various chicken tissues – liver, heart, breast, and gizzard with respective Young's moduli being 1.97, 9.47, 19.55, and 96.36 kPa. This sensor successfully differentiated between tissue types non-invasively, without requiring substantial deformation or penetration of the tissues. Given its piezoelectric nature, the sensor also holds significant potential for miniaturization through Micro-Electro-Mechanical Systems technology (MEMS), broadening its applicability in surgical environments.

Soft Tissue Compliance Detection in Minimally Invasive Surgery: Dynamic Measurement with Piezoelectric Sensor Based on Vibration Absorber Concept Hashem, Radwa; El-Hussieny, Haitham; Umezu, Shinjiro; El-Bab, Ahmed M. R. Fath
Journal of Robotics and Control (JRC) Vol. 5 No. 5 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i5.22895

Recent research in the medical field has increasingly focused on tissue repair, tumor detection, and associated therapeutic techniques. A significant challenge in Minimally Invasive Surgery (MIS) is the loss of direct tactile sensation by surgeons, as they cannot physically feel the organs they operate on. Tactile feedback enhances patient safety by tissue differentiation and reducing inadvertent damage risks. Addressing this challenge, this study introduces a novel tactile sensor designed for compliance detection to enhance tactile feedback in MIS. The sensor operates on a 2-Degree-of-Freedom (2-DOF) vibration absorber system, utilizing a piezoelectric actuator with a calibrated stiffness of 188 N/m. It interprets tissue stiffness regarding a spring constant, Ko, and measures changes in soft tissue stiffness by analyzing variations in the vibration absorber frequency, specifically at the frequency which causes the first mass to exhibit zero amplitude. The effectiveness of this sensor was evaluated through tests on polydimethylsiloxane (PDMS) specimens, which were engineered to replicate varying stiffness found in human organ tissues. Young's modulus of these specimens was determined using a universal testing machine, showing a range from 10.12 to 226.89 kPa. Additionally, the sensor was applied to measure the stiffness of various chicken tissues – liver, heart, breast, and gizzard with respective Young's moduli being 1.97, 9.47, 19.55, and 96.36 kPa. This sensor successfully differentiated between tissue types non-invasively, without requiring substantial deformation or penetration of the tissues. Given its piezoelectric nature, the sensor also holds significant potential for miniaturization through Micro-Electro-Mechanical Systems technology (MEMS), broadening its applicability in surgical environments.

Robot-Assisted Upper Limb Rehabilitation Using Imitation Learning Auta, Ismail Ashiru; Fares, Ahmed; Iwata, Hiroyasu; El-Hussieny, Haitham
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.23927

Robotic rehabilitation offers an innovative approach to enhance motor function recovery in patients with upper-limb impairment. However, the primary challenge lies in the development of adaptive and personalized therapies to meet the unique needs of patients. In response to this challenge, this paper presents a Rehabilitation Learning from Demonstration (RLfD) framework, which integrates Dynamic Movement Primitives (DMP) for learning and generalizing movements, and a Model Reference Adaptive Controller (MRAC) for real-time adaptive control. This combination enables a two-link manipulator to accurately replicate and adapt therapist demonstrations specifically designed for upper-limb rehabilitation. Unlike conventional task-specific controllers, which are limited by poor adaptability, minimal feedback, and lack of generalization, our system dynamically adjusts robotic assistance in real time based on the subject’s tracking error to optimize therapy outcomes. The objective is to minimize assistance while maximizing patient participation in the rehabilitation process. To facilitate this, the framework employs visual tracking technology to capture therapist demonstrations accurately. Once captured, the DMP component of the framework learns from these movements and generalizes them to new goals, while maintaining the original motion patterns. Our evaluations with a simulated two-link manipulator demonstrated the framework’s precise trajectory tracking, robust generalization, and adaptability to disturbances mimicking patient impairments. These tests confirmed the system’s ability to follow complex trajectories and adapt to dynamic patient motor functions. The promising results from these evaluations highlight our approach’s potential to significantly enhance adaptability and generalization in variable patient conditions, marking a substantial improvement over conventional systems.

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