An Optimization-Based Algorithm for Trajectory Planning of an Under-Actuated Robotic Arm to Perform Autonomous...

Area of Science:

• Robotics
• Minimally Invasive Surgery
• Surgical Automation

Background:

• Robot size is critical in single-port access surgeries due to limited workspace, often necessitating under-actuated designs.
• Suturing is a complex surgical task that typically demands full actuation, posing a challenge for under-actuated robotic systems.

Purpose of the Study:

• To develop and implement an optimization-based algorithm enabling autonomous suturing for under-actuated surgical robots.
• To address the limitations of under-actuated robots in performing complex tasks like suturing within confined surgical environments.

Main Methods:

• An optimization-based algorithm was designed to approximate ideal suturing trajectories.
• The algorithm allows for slight needle reorientation while minimizing deviation from a full degree-of-freedom path.
• Path deviation was analyzed based on suturing start location and needle size.

Main Results:

• The algorithm successfully maximized the accuracy of a four-DOF robot for path-constrained suturing.
• Cumulative path deviation was less than 10 mm in 13% of the workspace and less than 30 mm in the remainder.
• Needle radius significantly impacted deviation: 2.2 mm for a 10 mm radius vs. 8 mm for a 20 mm radius.

Conclusions:

• The optimization algorithm effectively enhances the suturing accuracy of under-actuated robots.
• The study highlights a correlation between workspace location, needle size, and achievable suturing accuracy.
• This approach offers a viable solution for complex surgical tasks using size-constrained robotic systems.