Optimization based trajectory planning for real-time 6DoF robotic patient motion compensation systems

Abstract

PurposeRobotic stabilization of a therapeutic radiation beam with respect to a dynamically moving tumor target can be accomplished either by moving the radiation source, the patient, or both. As the treatment beam is on during this process, the primary goal is to minimize exposure of normal tissue to radiation as much as possible when moving the target back to the desired position. Due to the complex mechanical structure of 6 degree-of-freedom (6DoF) robots, it is not intuitive as to what 6 dimensional (6D) correction trajectory is optimal in achieving such a goal. With proportional-integrative-derivative (PID) and other controls, the potential exists that the controller may generate a trajectory that is highly curved, slow, or suboptimal in that it leads to unnecessary exposure of healthy tissue to radiation. This work investigates a novel feedback planning method that takes into account a robot’s mechanical joint structure, patient safety tolerances, and other system constraints, and performs real-time optimization to search the entire 6D trajectory space in each time cycle so it can respond with an optimal 6D correction trajectory.MethodsComputer simulations were created for two 6DoF robotic patient support systems: a Stewart-Gough platform for moving a patient’s head in frameless maskless stereotactic radiosurgery, and a linear accelerator treatment table for moving a patient in prostate cancer radiation therapy. Motion planning was formulated as an optimization problem and solved at real-time speeds using the L-BFGS algorithm. Three planning methods were investigated, moving the platform as fast as possible (platform-D), moving the target along a straight-line (target-S), and moving the target based on the fastest descent of position error (target-D). Both synthetic motion and prior recorded human motion were used as input data and output results were analyzed.ResultsFor randomly generated 6D step-like and sinusoidal synthetic input motion, target-D planning demonstrated the smallest net trajectory error in all cases. On average, optimal planning was found to have a 45% smaller target trajectory error than platform-D control, and a 44% smaller target trajectory error than target-S planning. For patient head motion compensation, only target-D planning was able to maintain a ≤0.5mm and ≤0.5deg clinical tolerance objective for 100% of the treatment time. For prostate motion, both target-S planning and target-D planning outperformed platform-D control.ConclusionsA general 6D target trajectory optimization framework for robotic patient motion compensation systems was investigated. The method was found to be flexible as it allows control over various performance requirements such as mechanical limits, velocities, acceleration, or other system control objectives.

Biomechanics Analysis of the Lower Limbs in 20 Male Sprinters Using the International Society of Biomechanics Six-Degrees-of-Freedom Model and the Conventional Gait Model

“…The relationship between the foot strike mode, the lower-limb mechanics, and the risk of injury has been extensively studied [ 31 – 33 ]. Significant differences exist between athletes using habitual UPSS-FF and UPSS-RF foot strike patterns [ 34 ].…”

Robotic Systems in Radiotherapy and Radiosurgery

“…They extended this work by proposing a custom soft robot with compliant components for more precise and comfortable motion compensation [20]. Furthermore, they introduced a control strategy for motion compensation to minimize total deviation from the target pose based on the dynamic properties of the specific robot used [21]. Here, they used the L-BFGS optimization algorithm to find trajectories that could keep head or prostate motion within 0.5-mm deviation 100% of the time.…”

Rehabilitasyon Hizmetlerinde Yapay Zekâ Uygulamaları

“…Günümüzde yapılan son araştırmalar, hareketli bir taban platform üzerinde akıllı robot uygulamaları kullanarak (Şekil 3) daha sık antrenman yapımına imkân sağlayan robotik platformların ortaya çıkmasını sağlamıştır. Bu kapsamda üretilen Stewart Platformu; ayak bileği, diz ve eklemleri hareketlendirmek sağlığına kavuşturmak veya rehabilite etmek amacıyla kullanılmaktadır (Budaklı & Yılmaz, 2021;Joe et al, 2021;Kim et al, 2019;X. Liu & Wiersma, 2019;Yang et al, 2015).…”