Design and Control of a Highly Redundant Rigid-Flexible Coupling Robot to Assist the COVID-19 Oropharyngeal-Swab Sampling
Y. Hu et al.
The outbreak of novel coronavirus pneumonia (COVID-19) has caused mortality and morbidity worldwide. Oropharyngeal-swabs (OP-swab) sampling is widely used for the diagnosis of COVID-19 in the world. To avoid the clinical staff from being affected by the virus, we developed a 9-DOFs rigid-flexible coupling (RFC) robot to assist the COVID19 OP-swab sampling. This robot composes of a visual system, a UR5 robot arm, a mi...
Modeling and Balance Control of Supernumerary Robotic Limb for Overhead Tasks
J. Luo et al.
Overhead manipulation tasks often require collaborations between two operators, which becomes challenging in confined spaces such as in a compartment. Supernumerary Robotic Limb (SuperLimb), as a promising wearable robotic solution, can provide assistance in terms of broader workspace, wider manipulation functionalities and safer working conditions. However, the safety concerns of human-centered SuperLimb interaction...
Decentralized Ability-Aware Adaptive Control for Multi-Robot Collaborative Manipulation
L. Yan, T. Stouraitis and S. Vijayakumar
Multi-robot teams can achieve more dexterous, complex and heavier payload tasks than a single robot, yet effective collaboration is required. Multi-robot collaboration is extremely challenging due to the different kinematic and dynamics capabilities of the robots, the limited communication between them, and the uncertainty of the system parameters. In this letter, a Decentralized Ability-Aware Adaptive Control (DA 3 ...
Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment
X. Guo, J. Hu, J. Chen, F. Deng and T. L. Lam
The core problem of visual multi-robot simultaneous localization and mapping (MR-SLAM) is how to efficiently and accurately perform multi-robot global localization (MR-GL). The difficulties are two-fold. The first is the difficulty of global localization for significant viewpoint difference. Appearance-based localization methods tend to fail under large viewpoint changes. Recently, semantic graphs have been utilized ...
UniFuse: Unidirectional Fusion for 360° Panorama Depth Estimation
H. Jiang, Z. Sheng, S. Zhu, Z. Dong and R. Huang
Learning depth from spherical panoramas is becoming a popular research topic because a panorama has a full field-of-view of the environment and provides a relatively complete description of a scene. However, applying well-studied CNNs for perspective images to the standard representation of spherical panoramas, i.e., the equirectangular projection, is suboptimal, as it becomes distorted towards the poles. Another rep...
Towards Fully Autonomous Ultrasound Scanning Robot With Imitation Learning Based on Clinical Protocols
Y. Huang, W. Xiao, C. Wang, H. Liu, R. Huang and Z. Sun
Ultrasound scanning plays an important role in modern clinical examinations. Thanks to its small footprint, low cost, and popularity, it has been widely used in annual physical examinations and many other diagnosis and intervention procedures. However, the scanning results depend heavily on the clinician operators’ skills, causing inconsistency and even false detection. A fully autonomous ultrasound scanning robot ca...
RigidFusion: Robot Localisation and Mapping in Environments With Large Dynamic Rigid Objects
R. Long, C. Rauch, T. Zhang, V. Ivan and S. Vijayakumar
This work presents a novel RGB-D SLAM approach to simultaneously segment, track and reconstruct the static background and large dynamic rigid objects that can occlude major portions of the camera view. Previous approaches treat dynamic parts of a scene as outliers and are thus limited to a small amount of changes in the scene, or rely on prior information for all objects in the scene to enable robust camera tracking....
A Two-stage Unsupervised Approach for Low light Image Enhancement
J. Hu, X. Guo, J. Chen, G. Liang, F. Deng and T. L. Lam
As vision based perception methods are usually built on the normal light assumption, there will be a serious safety issue when deploying them into low light environments. Recently, deep learning based methods have been proposed to enhance low light images by penalizing the pixel-wise loss of low light and normal light images. However, most of them suffer from the following problems: 1) the need of pairs of low light ...
Dynamic Modeling of Magnetic Helical Microrobots
X. Wang, C. Hu, S. Pane and B. J. Nelson
Magnetic helical microrobots that can be driven by low-strength rotating magnetic fields have found wide applications, particularly in biomedical research. The motion dynamics of magnetic helical microrobots is critical for their intelligent control and for performing different tasks in complex environments. These microrobots convert rotational motion into translational motion along their central axis. Many factors c...
V-stability Based Control for Energy-saving Towards Long Range Sailing
Q. Sun, W. Qi, X. Ji and H. A. Qian
Ensuring an adequate supply of energy is a challenge in the development of autonomous sailboats for long-range sailing capability, as the continuous high-frequency execution of control commands leads to high energy consumption. However, as the control of sailboat is much more complex than the other USVs, especially in a complicated and windy environment, simply reducing control frequency will lead to large path track...
Modeling and Control of a Hybrid Wheeled Jumping Robot
Traiko Dinev1 , Songyan Xin1 , Wolfgang Merkt1,2 , Vladimir Ivan1 , and Sethu Vijayakumar1,3
In this paper, we study a wheeled robot with a prismatic extension joint. This allows the robot to build up momentum to perform jumps over obstacles and to swing up to the upright position after the loss of balance. We propose a template model for the class of such two-wheeled jumping robots. This model can be considered as the simplest wheeled-legged system. We provide an analytical derivation of the system dynamics...
Multi-mode Trajectory Optimization for Impact-aware Manipulation
Theodoros Stouraitis∗,1,2, Lei Yan∗,1, Joao Moura1, Michael Gienger2, and Sethu Vijayakumar1,3
The transition from free motion to contact is a challenging problem in robotics, in part due to its hybrid nature. Additionally, disregarding the effects of impacts at the motion planning level often results in intractable impulsive contact forces. In this paper, we introduce an impact-aware multi-mode trajectory optimization (TO) method that combines hybrid dynamics and hybrid control in a coherent fashion. A key co...