A Clinical Dataset for the Evaluation of Motion Planners in Medical Applications

10/19/2022
by   Inbar Fried, et al.
0

The prospect of using autonomous robots to enhance the capabilities of physicians and enable novel procedures has led to considerable efforts in developing medical robots and incorporating autonomous capabilities. Motion planning is a core component for any such system working in an environment that demands near perfect levels of safety, reliability, and precision. Despite the extensive and promising work that has gone into developing motion planners for medical robots, a standardized and clinically-meaningful way to compare existing algorithms and evaluate novel planners and robots is not well established. We present the Medical Motion Planning Dataset (Med-MPD), a publicly-available dataset of real clinical scenarios in various organs for the purpose of evaluating motion planners for minimally-invasive medical robots. Our goal is that this dataset serve as a first step towards creating a larger robust medical motion planning benchmark framework, advance research into medical motion planners, and lift some of the burden of generating medical evaluation data.

READ FULL TEXT

page 2

page 3

research
03/07/2020

Experimental Comparison of Global Motion Planning Algorithms for Wheeled Mobile Robots

Planning smooth and energy-efficient motions for wheeled mobile robots i...
research
10/17/2021

Characterizing and Improving the Resilience of Accelerators in Autonomous Robots

Motion planning is a computationally intensive and well-studied problem ...
research
11/06/2020

Reactive motion planning with probabilistics safety guarantees

Motion planning in environments with multiple agents is critical to many...
research
08/07/2023

Robots as AI Double Agents: Privacy in Motion Planning

Robotics and automation are poised to change the landscape of home and w...
research
12/13/2021

MotionBenchMaker: A Tool to Generate and Benchmark Motion Planning Datasets

Recently, there has been a wealth of development in motion planning for ...
research
03/03/2022

The RATTLE Motion Planning Algorithm for Robust Online Parametric Model Improvement with On-Orbit Validation

Certain forms of uncertainty that robotic systems encounter can be expli...
research
09/24/2019

Graph Policy Gradients for Large Scale Unlabeled Motion Planning with Constraints

In this paper, we present a learning method to solve the unlabelled moti...

Please sign up or login with your details

Forgot password? Click here to reset