12 accepted papers
Self-supervised monocular depth estimation has achieved notable success under daytime conditions. However, its performance deteriorates markedly at night due to low visibility and varying illumination, e.g., insufficient light causes textureless areas, and moving objects bring blurry regions. To thi
Self-supervised monocular depth estimation has achieved notable success under daytime conditions. However, its performance deteriorates markedly at night due to low visibility and varying illumination, e.g., insufficient light causes textureless areas, and moving objects bring blurry regions. To thi…
Minimally Invasive Surgery has advanced surgical practice, yet early-stage gastrointestinal cancer treatment remains challenging. Endoscopic Submucosal Dissection offers a solution but faces maneuverability constraints in complex anatomical environments. This paper presents a novel inflatable soft r
In recent years, the area of Robot-Assisted Minimally Invasive Surgery (RAMIS) is standing on the the verge of a new wave of innovations. However, autonomy in RAMIS is still in a primitive stage. Therefore, most surgeries still require manual control of the endoscope and the robotic instruments, res…
Due to the visual properties of reflection and refraction, RGB-D cameras cannot accurately capture the depth of transparent objects, leading to incomplete depth maps. To fill in the missing points, recent studies tend to explore new visual features and design complex networks to reconstruct the dept
In recent years, Robot-Assisted Minimally Invasive Surgery (RAMIS) has been widely adopted worldwide due to its high precision, improved ergonomics and intuitive control. With the advances in artificial intelligence and surgical robot technologies, it is anticipated that the cognitive load on the su
Human-robot shared control, which integrates the advantages of both humans and robots, is an effective approach to facilitate efficient surgical operation. Learning from demonstration (LfD) techniques can be used to automate some of the surgical sub tasks for the construction of the shared control m…
Transparent objects with unique visual properties often make depth cameras fail to scan their reflective and refractive surfaces. Recent studies on depth completion of transparent objects have leveraged a linear system based on the geometric constraints to predict the missing depth, which is hard to…
The assessment of microsurgical skills for Robot-Assisted Microsurgery (RAMS) still relies primarily on subjective observations and expert opinions. A general and automated evaluation method is desirable. Deep neural networks can be used for skill assessment through raw kinematic data, which has the
The recent development of Robot-Assisted Minimally Invasive Surgery (RAMIS) has brought much benefit to ease the performance of complex Minimally Invasive Surgery (MIS) tasks and lead to more clinical outcomes. Compared to direct master-slave manipulation, semi-autonomous control for the surgical ro…
Accurate master-slave control is important for Robot-Assisted Microsurgery (RAMS). This paper presents a handheld master controller for the operation and training of RAMS. A 9-axis Inertial Measure Unit (IMU) and a micro camera are utilized to form the sensing system for the handheld controller. A n…
Learning manipulations from videos is an inspiriting way for robots to acquire new skills. In this paper, we propose a framework that can generate robotic manipulation plans by observing human demonstration videos without special marks or unnatural demonstrated behaviors. More specifically, the fram…