Projects
Projects
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Below are the key projects I’ve worked on. Scroll down to see my presentation for more details of my contributions.
Detection of Motion Anomalies in Real Time
Developing a machine learning model to detect joint disorders and movement impairments in real time using standard video cameras.
Synthesis of Leg Mechanism and Optimal Design of Walking Robot with Decoupled Motion
Synthesis of Leg Mechanism and Optimal Design of Walking Robot with Decoupled Motion
Novelty:
Novelty:
the development of synthesis methods and optimization of walking robot’s (WR) structural and metric parameters based on functional division of motors, which allows:
Simplification of leg coordination and minimization of number of motors, lowering energy consumption;
Addressing the issue of adapting each foot to surface irregularities individually and independently of the main control unit;
Resolving the problem of redundant constraints in existing designs and eliminating parasitic loads on actuating mechanisms associated with multiple static indeterminacies;
Eliminating energy expenditures on foot slippage and reducing reaction forces at joints during turns;
Optimization of robot turning based on isotropy criterion.
Structural and Parametric Synthesis of the Lower Limb Exoskeleton
Structural and Parametric Synthesis of the Lower Limb Exoskeleton
Novelty:
Novelty:
Innovative Mechanical Design:
Combined-type structure that is energy-efficient, simple, compact, and structurally rigid.
Minimal trajectory deviation under external disturbances, ensuring enhanced operational safety.
Human-Centric Optimization:
Compatibility with human metrics and motion parameters achieved through advanced structure and multi-criteria optimization.
Feedback Control:
Utilizes EMG signals to enable dynamic, real-time feedback control.
Intelligent Data Analysis:
Incorporates deep learning algorithms (e.g., Convolutional Neural Networks) to analyze sensor data, ensuring precise patient status determination and enabling real-time adaptation of rehabilitation protocols.
Medical Robots and AI for Advancing Diagnostic and Treatment Systems During the Pandemic
The robotic complex consists of four autonomous robots:
Saliva Sampling Parallel Manipulator
Patient Care Assistant
High Payload Transporter
Autonomous Disinfector with Microreactor System
Complex Intelligent Robotization of Technological Processes of Uranium Production
Project goal:
Development of a robotic complex (RTK-TUK-118) to perform the entire cycle of operations, starting from removing and closing the lid, evenly filling HCPU, taking samples, and ending with closing the lid. This is to replace manual labor and minimize the risk of injuries and increased radiation doses that occur when manually performing operations related to concentrated uranium solutions and other products (HCPU – chemical concentrate of natural uranium, U3O8 - uranium oxide, and others).
Development of a Rod Pumping Unit Drives for the Oil Extraction
The novelty lies in eliminating several drawbacks in existing designs:
Horse-head (arc-head), is massive and structurally complex and demands high manufacturing accuracy
Using a flexible link to connect the mechanism to the gland rod, wound on the balancer head, adds complexity
Sensitivity to vibrations of pumping unit
The high balancer attachment point (upper base) poses a significant drawback. Reactions in the balancer sway the base, necessitating a massive, high-quality concrete foundation and increasing metal consumption.
Poor balancing causes shock loads on the crank finger, alternating load signs, and gearbox wear.
Increasing stroke via crank length results in inefficient force transmission at small motion angles and large hinge reactions.
Development of Robots, Scientific, Technical Solutions, and Software for Flexible Robotization and Industrial Automation in Automotive Enterprises with Artificial Intelligence Integration
Autonomous Robotic Femoral Fracture Reduction
Autonomous Robotic Femoral Fracture Reduction
Outcomes:
Enhanced surgical precision and improved patient safety by ensuring optimal fracture reduction with minimal tissue damage.
Key technologies:
Utilizes parallel structure for high precision;
Utilizes 2D X-ray imaging to reconstruct a 3D bone model for trajectory planning.
The system identifies corresponding points on fractured segments
Computes an optimal surgical trajectory that minimizes risk to surrounding tissues and bone.
Quantification of the Neuromechanical Control of Human Gait using Self-Supervised Learning
Quantification of the Neuromechanical Control of Human Gait using Self-Supervised Learning
Collaborative research with Columbia University
and National Rehabilitation Center.
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