A review on machine learning in flexible surgical and interventional robots: Where we are and where we are going

Minimally Invasive Procedures (MIPs) emerged as an alternative to more invasive surgical approaches, offering patient benefits such as smaller incisions, less pain, and shorter hospital stay. In one class of MIPs, where natural body lumens or small incisions are used to access deeper anatomical locations, Flexible Surgical and Interventional...

Control of Multi-Degree-of-Freedom Catheters in Unknown Environments: Exploring the Potential of Deep Learning and Augmented Reality

Cardiovascular disease is currently one of the biggest threats to health. Specific types of cardiovascular disease include, but are not limited to, coronary artery disease, cardiac valve disorders, or peripheral arterial disease. The current gold standard for managing these conditions incorporates the use of catheters and guidewires for...

Risk-Aware Decentralized Multi-MAV Planning in Unknown and Dynamic Environments

Recent progress in multiple micro aerial vehicle (MAV) systems has demonstrated autonomous navigation in static environments. Yet, there are limited works regarding the autonomous navigation of multiple MAVs in dynamic and unknown environments. The challenge arises from the complexity of the motion planning problem, which requires the MAVs to...

Model Predictive Path Planning of AGVs: Mixed Logical Dynamical Formulation and Distributed Coordination

Most of the existing path planning methods of automated guided vehicles (AGVs) are static. This paper proposes a new methodology for the path planning of a fleet of AGVs to improve the flexibility, robustness, and scalability of the AGV system. We mathematically describe the transport process as a dynamical system using an ad hoc mixed...

Shape Sensing of Flexible Robots Based on Deep Learning

In this article, a deep learning method for the shape sensing of continuum robots based on multicore fiber bragg grating (FBG) fiber is introduced. The proposed method, based on an artificial neural network (ANN), differs from traditional approaches, where accurate shape reconstruction requires a tedious characterization of many...

A Secure Robot Learning Framework for Cyber Attack Scheduling and Countermeasure

The problem of learning-based control for robots has been extensively studied, whereas the security issue under malicious adversaries has not been paid much attention to. Malicious adversaries can invade intelligent devices and communication networks used in robots, causing incidents, achieving illegal objectives, and even injuring people....

Sensor Fusion for Shape Reconstruction Using Electromagnetic Tracking Sensors and Multi-Core Optical Fiber

Optical fiber-based shape sensing is gaining popularity in cardiac catheterization lately. Typically, these procedures are taking place under the guidance of fluoroscopy. However, fluoroscopy has several disadvantages. Thanks to fiber optic shape sensing and Electromagnetic Tracking (EMT), the 3D catheter shape can now be tracked in real-time...

Deep-Learning-Based Compliant Motion Control of a Pneumatically-Driven Robotic Catheter

In cardiovascular interventions, when steering catheters and especially robotic catheters, great care should be paid to prevent applying too large forces on the vessel walls as this could dislodge calcifications, induce scars or even cause perforation. To address this challenge, this paper presents a novel compliant motion control algorithm...

A multi-axis robot-based bioprinting system supporting natural cell function preservation and cardiac tissue fabrication

Despite the recent advances in artificial tissue and organ engineering, how to generate large size viable and functional complex organs still remains as a grand challenge for regenerative medicine. Three-dimensional bioprinting has demonstrated its advantages as one of the major methods in fabricating simple tissues, yet it still faces...

OpenFish: Biomimetic design of a soft robotic fish for high speed locomotion

We present OpenFish: an open source soft robotic fish which is optimized for speed and efficiency. The soft robotic fish uses a combination of an active and passive tail segment to accurately mimic the thunniform swimming mode. Through the implementation of a novel propulsion system that is capable of achieving higher oscillation frequencies...

Hysteresis Modeling of Robotic Catheters based on Long Short-Term Memory Network for Improved Environment Reconstruction

Catheters are increasingly being used to tackle problems in the cardiovascular system. However, positioning precision of the catheter tip is negatively affected by hysteresis. To ensure tissue damage due to imprecise positioning is avoided, hysteresis is to be understood and compensated for. This work investigates the feasibility to model...

Biomimetic design of a soft robotic fish for high speed locomotion

We present a novel DC motor driven soft robotic fish which is optimized for speed and efficiency based on experimental, numerical and theoretical investigation into oscillating propulsion. Our system achieves speeds up to 0.85 m/s, outperforming the previously reported fastest free swimming soft robotic fish by a significant margin of 27%. A...

Color-Based Proprioception of Soft Actuators Interacting with Objects

Actuators using soft materials feature a large number of degrees of freedom. This tremendous flexibility allows a soft actuator to passively adapt its shape to the objects under interaction. In this paper, we propose a novel proprioception method for soft actuators during real-time interaction with previously unknown objects. First, we design...

A video-based assessment of likeability and usability in a play application of robots for children

Purpose: The purpose of this paper is to conduct research with children, who have different abilities from adults, in terms of language understanding and level of attention, is a challenging task, especially concerning novel interactive systems such as social robots. Consequently, self-reporting methods are often replaced or supplemented by...

Adapting Robot Architecture for Pick and Place

Pick and place robots are very popular in industry as they provide speedy and precise handling applications. They are especially practical in repetitive work as they can work long time with a faster and more accuracy motion than humans. Compared with serial manipulator, parallel robots have the advantages of high accuracy, high rigidity and high...