UWB and IMU fusion positioning methods have been widely concerned for its high accuracy and robustness in GNSS-denied environment. However, most of the existing methods are stay under the Markov assumption and ignore the credible estimation of the yaw angle. In this paper, we propose a novel tightly-coupled IMU and multiple UWB tags fusion framework based on a graph optimization model that is able to provide high precision positioning and attitude determination service, which provides a new technical approach for the practical application of UWB and IMU fusion. A relative rotation and motion state initialization algorithm is designed and presented, which solves the problems that IMU installation direction is difficult to measure and the initial state is not stationary in practical application. Simulation experiments shows the impact of UWB tags distribution distance and IMU noise parameters on system performance, which provides design reference for practical applications. Finally, the real-site experiment proves the positioning RMSE of 4 cm based on our fusion solution and these simulation evidences, which confirms the great performance of our fusion solution.

The relative pose estimation is one of the most fundamental components for multi-robot systems, while it still remains an open and challenging research topic in infrastructure-free environment. In this letter, we target improving the accuracy and robustness of relative pose estimation for ground robotic teams, and propose to fuse range and odometry measurements to estimate the relative pose using sliding window optimization. In the system, multiple UWB tags for ranging are equipped on each robot, and visual inertial odometry is applied for estimating the ego-motion pose for each robot. Aiming for simple and effective relative pose initialization, the triangulation uncertainty for multi-tag robots is analyzed, and an initialization method is designed. To cope with the complex environments such as continuous NLOS condition, a NLOS detection and range measurements filtering method is presented. We have conducted series of experiments to demonstrate the performance of the proposed approach.

A tactile sensor is an indispensable component for electronic skin, mimicking the sensing function of organism skin. Various sensing materials and microstructures have been adopted in the fabrication of tactile sensors. Herein, we propose a highly sensitive flexible tactile sensor composed of nanocomposites with pyramid and irregularly rough microstructures and implement a comparison of piezoresistive properties of nanocomposites with varying weight proportions of multi-wall nanotubes and carbon black particles. In addition to the simple and low-cost fabrication method, the tactile sensor can reach high sensitivity of 3.2 kPa⁻¹ in the range of <1 kPa and fast dynamic response of 217 ms (loading) and 81 ms (recovery) at 40 kPa pressure. Moreover, body movement monitoring applications have been carried out utilizing the flexible tactile sensor. A sound monitoring application further indicates the potential for applications in electronic skin, human–computer interaction, and physiological detection.

Nowadays, accurate and robust localization is preliminary for achieving a high autonomy for robots and emerging applications. More and more, sensors are fused to guarantee these requirements. A lot of related work has been developed, such as visual-inertial odometry (VIO). In this research, benefiting from the complementary sensing capabilities of IMU and cameras, many problems have been solved. However, few of them pay attention to the impact of different performance IMU on the accuracy of sensor fusion. When faced with actual scenarios, especially in the case of massive hardware deployment, there is the question of how to choose an IMU appropriately? In this paper, we chose six representative IMUs with different performances from consumer-grade to tactical grade for exploring. According to the final performance of VIO based on different IMUs in different scenarios, we analyzed the absolute trajectory error of Visual-Inertial Systems (VINS_Fusion). The assistance of IMU can improve the accuracy of multi-sensor fusion, but the improvement of fusion accuracy with different grade MEMS-IMU is not very significant in the eight experimental scenarios; the consumer-grade IMU can also have an excellent result. In addition, the IMU with low noise is more versatile and stable in various scenarios. The results build the route for the development of Inertial Navigation System (INS) fusion with visual odometry and at the same time, provide a guideline for the selection of IMU.

Fast and flexible dense reconstruction has been extensively studied due to its wide application. Considering the efficiency of multi-robot systems, cooperative reconstruction is gaining attention. Classic methods rely on inter-robot loop closures, which cannot work when there is no common area between robots. Ultra-wideband sensors provide distance measurement and can replace loop closures in multi-robot systems. However, ranging-based schemes do not solve the inconsistency of reconstruction, which is caused by odometry drift. We propose a range-aided cooperative localization and consistent reconstruction system. First, the system's front end tightly couples visual odometry and ranging to perform loop-independent cooperative reconstruction and reduce odometry drift. Second, the back end detects overlapping regions in submaps and proposes a novel dense pose graph optimization (PGO) step to further eliminate all trajectory drift and achieve consistent reconstruction. Extensive field experiments demonstrate the effectiveness and high performance of the system.

With the increasing demand for total knee arthroplasty (TKA) surgery, more attention has been paid to the accurate measurement of pressure and adjustment of knee prosthesis. The tightness between artificial meniscus and articular head and the thickness of artificial meniscus will directly affect the matching between knee joint and human body. At present, the installation and adjustment of knee joint during operation largely depends on the personal experience of doctors. In this work, a flexible pressure sensing device with bendable and distortable sensor arrays for force detection in knee arthroplasty is fabricated and characterized to provide quantitative data guidance and reference for knee arthroplasty. The internal pressure of prosthesis knee joint can be effectively detected through real-time obtaining for output voltages of sensor array. The densely distributed measuring points feedback abundant pressure distribution information. The pressure device shows good repeatability, consistency and small hysteresis in large detection range and stability in dynamic response which indicates promising potential in applications of knee arthroplasty.