Surgical robots are already used in operating rooms around the world, helping surgeons perform complex procedures with remarkable precision.
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surgeons → use → precision
But these machines are still controlled by human surgeons.
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machines → control → surgeons
Now, an 18-year-old student from Texas has explored what it could take to teach a surgical robot to carry out one of the most delicate tasks in medicine: identifying and removing a tumour on its own.
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it → explore → own
According to the Society for Science, Rayhan Papar, an 18-year-old student from Spring, Texas, developed a framework to help surgical robots learn autonomous tumour removal.
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robots → accord → removal
His project, titled
Sim-to-Real for Autonomous Tumor Resection via Minimally Invasive Robotics, was tested on a da Vinci surgical system and successfully removed whole tumours in three of four gel-model tests.
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project → title → tests
Papar was also named a finalist in the Regeneron Science Talent Search 2026.
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Papar → name → Search
Teaching a robot to operate
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robot → teach → ?
The idea behind Papar's project was not to replace surgeons or create a robot ready to perform operations on patients.
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idea → replace → patients
Instead, his work focused on one of the biggest challenges in surgical robotics: how to train a machine to deal with the unpredictable conditions found inside the human body.
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work → focus → body
A surgical robot cannot simply follow the same set of instructions every time.
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robot → follow → instructions
Every patient's anatomy is different, and soft tissues can move, deform and change shape during a procedure.
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tissues → move → procedure
They also have to operate within a restricted visual field, while tissues can move and change size and shape during surgery.
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tissues → have → surgery
These factors make it difficult to train a robot to carry out a task independently.
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it → make → task
Papar's solution was to begin in a simulated environment rather than directly training the robot in the physical world.
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solution → begin → world
He created a physics-based simulation using medical imaging to reconstruct anatomy.
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He → create → anatomy
Within this virtual environment, the robot could learn how to approach and remove a tumour while accounting for the physical behaviour of tissues and the constraints of minimally invasive surgery.
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robot → learn → surgery
In simple terms, the robot was first given an opportunity to learn and make decisions in a computer-generated surgical setting before those lessons were transferred to a real robotic system.
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lessons → give → system
From simulation to the da Vinci system
This process is often described as a “sim-to-real” approach.
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process → describe → approach
The aim is to use simulation as a safer and more practical training ground before testing whether the robot's learned skills can work in the physical world.
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skills → use → world
The framework was designed to bridge the gap between simulation and real-world robotic performance, allowing the system to apply its virtual learning to a physical robotic platform.
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system → design → platform
The framework was then tested on a da Vinci surgical system, a robotic platform designed for minimally invasive surgery.
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framework → test → surgery
In four gel-model tests, the system achieved complete tumour removal in three cases, according to the Society for Science.
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system → achieve → Science
These were not human patients, and the results do not mean that an autonomous surgical robot is now ready for use in hospitals.
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robot → mean → hospitals
Gel models provide a controlled experimental setting, allowing researchers to test a robotic system's performance before attempting more complex and clinically relevant studies.
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researchers → provide → studies
Still, achieving complete tumour removal in three of the four tests offers an early demonstration of how simulation-based training could help robots perform highly specialised surgical tasks.
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robots → achieve → tasks
Why the research matters
Surgical robots can offer precision and dexterity, particularly in procedures performed through small incisions.
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robots → matter → incisions
However, human surgeons remain responsible for operating these systems and making critical decisions during surgery.
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surgeons → remain → surgery
Research such as Papar's explores whether some parts of a surgical procedure could eventually become more autonomous.
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parts → explore → procedure
Before that could happen, however, robots would need to reliably understand changing anatomy, adapt to moving and deformable tissue, recognise surgical targets and respond safely when conditions do not match expectations.
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conditions → happen → expectations
That is where the simulation component of Papar's work becomes significant.
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component → become → work
Training in a virtual environment could potentially allow robotic systems to encounter many different surgical scenarios before being tested in physical models.
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systems → allow → models
The project also highlights the growing intersection of robotics, computer science, medical imaging and surgery.
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project → highlight → robotics
Rather than treating a surgical robot as a machine that simply repeats programmed movements, the research explores how it might learn to make task-related decisions within a changing environment.
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it → treat → environment
Papar, who attends The Woodlands College Park High School, also holds a patent for a surgical aid designed to help with brain tumour resection, according to the Society for Science.
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who → attend → Science
Beyond his research, he mentors other students working on STEM projects and co-founded IdeaCharge, a nonprofit that teaches children about electrical engineering.
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that → mentor → engineering
His project is still an experimental research effort, and its results should be viewed in that context.
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results → view → context
How important do you believe simulation training is for surgical robots?
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training → believe → robots
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Share OpinionHowever, the experiment offers a glimpse into a possible future direction for surgical robotics, one in which machines may be trained extensively in realistic simulations before helping surgeons perform increasingly complex tasks.
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surgeons → share → tasks
For Papar, that future began with four gel-model tests, three successful tumour removals and a question that could shape the next generation of medical robotics: can a surgical robot learn not just to follow commands, but to make the right decisions when the surgical environment changes?
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environment → begin → decisions
The Aporia
