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...

Design of Child-robot Interactions for Comfort and Distraction from Post-operative Pain and Distress

There are numerous strategies for reducing the stress and anxiety associated with pain that children experience before and after surgery. There is a potential communication barrier between hospital staff and the child which may result in inadequate pain management. Social robots may reduce the gap between the support that personnel can...

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...

TSES-R: An Extended Scale for Measuring Parental Expectations toward Robots for Children in Healthcare

There is a growing interest in implementing robotics applications for children in healthcare to provide companionship, comfort, education, and therapy. Parental expectations regarding robotics for young children play a critical role in influencing its development and acceptance. However, parental expectations are widely overlooked in HRI....

Contour Moments Based Manipulation of Composite Rigid-Deformable Objects With Finite Time Model Estimation and Shape/Position Control

The robotic manipulation of composite rigid-deformable objects (i.e., those with mixed nonhomogeneous stiffness properties) is a challenging problem with clear practical applications that, despite the recent progress in the field, it has not been sufficiently studied in the literature. To deal with this issue, in this article, we propose a...

Efficient MSPSO Sampling for Object Detection and 6D Pose Estimation in 3D Scenes

The point pair feature (PPF) is widely used in industrial applications for estimating 6D poses of known objects from unrecognized point clouds. The key to the success of PPF matching is to establish correct 3D correspondences between the object and the scene, i.e., finding as many valid similar point pairs as possible. Thus, a set of...

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...

Barrier Function-based Safe Reinforcement Learning for Formation Control of Mobile Robots

Distributed model predictive control (DMPC) concerns how to online control multiple robotic systems with constraints effectively. However, the nonlinearity, nonconvexity, and strong interconnections of dynamic system models and constraints can make the real-time and real-world DMPC implementations nontrivial. Reinforcement learning (RL)...

Distributed Model Predictive Contouring Control for Real-Time Multi-Robot Motion Planning

Existing motion planning algorithms for multi-robot systems must be improved to address poor coordination and increase low real-time performance. This paper proposes a new distributed real-time motion planning method for a multi-robot system using Model Predictive Contouring Control (MPCC). MPCC allows separating the tracking accuracy and...

Understanding Design Preferences for Robots for Pain Management: A Co-Design Study

There is growing interest in psychological interventions using socially assistive robots to mitigate distress and pain in the pediatric population. This work seeks to address the deficit in understanding of what features and functionality young children and their parents desire to help with pain management by using co-design, a common...

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...

Steering Micro-Robotic Swarm by Dynamic Actuating Fields

We present a general solution for steering microrobotic<br/>swarm by dynamic actuating fields. In our approach, the<br/>motion of micro-robots is controlled by changing the actuating<br/>direction of a field applied to them. The time-series sequence<br/>of actuating field’s directions can be computed automatically.<br/>Given a target position in...