Simple virtual slip force sensor for walking biped robots

This paper presents a novel simple Virtual Slip Force Sensor (VSFS) for a walking biped. Bipeds walking stability is critical and they tend to lose it easily in real environments. Among the significant aspects that affect the stability is the availability of the required friction force which is necessary for the robot not to slip. In this paper we propose the use of the virtual sensor to detect the slip force. The design structure of the VSFS consists of two steps, in the first step it utilizes the measured acceleration of the center of mass (CoM) and the ZMP signals in the simple linear inverted pendulum model (LIPM) to estimate the position of the CoM, and in the second step the Newton law is employed to find the total ground reaction force (GRF) for each leg based on the position of CoM. Then both the estimated force and the measured force from the sensors assembled at the foot are used to detect the slip force. The validity of the proposed estimation method was confirmed by simulations on 3D dynamics model of the humanoid robot SURALP while walking. The results are promising and prove themselves well

The Importance of Human Motion for Simulation Testing of GNSS

Human motion is generally considered benign to the performance of global navigation satellite system (GNSS) and other positioning sensors. This study proves that this is not the case, even for typical human behaviour involving GNSS user equipment, e.g. in smartphones. Using recorded human motion, it is shown that phase-lock loops (PLLs) in GNSS receivers are sensitive to jerk dynamics induced by user motion, resulting in carrier cycle slips. To test the effects of human dynamics on GNSS carrier tracking, real human motion profiles were captured. These profiles comprised typical types of movements using a mobile phone, e.g. holding, answering and texting, different types of activities, e.g. walking or jogging, as well as different phone locations on the human body, e.g. in a hand, pocket, backpack and on an arm band. The data were captured outdoors using an Xsens MTi-G MEMS (Micro-Electronic Mechanical Systems) Inertial Measurement Unit (IMU) aided by a Global Positioning System (GPS) receiver with a 100Hz output rate. Then the captured motion (MoCap) was processed and input into a simulated PLL in Matlab with different tracking loop bandwidths (BL_CA) and carrier power-to-noise density ratios (C/N0). The results show that pedestrian gestures and type of activity, e.g. walking or jogging, affect the performance of the simulated PLL more adversely than the location of the phone on the human body. Also, to track pedestrian motion encompassing these gestures, activities and receiver locations, a minimum of 15Hz tracking bandwidth is required. Consequently, receiver manufacturers should exercise caution before reducing tracking bandwidths to compensate for the reduction in C/N0 resulting from GNSS antenna design, human body masking and the effects of buildings, trees and other environmental features. This paper also proposes and describes a pedestrian motion model (PMM) that simulates the GNSS antenna trajectory in 3D, when it is held by or attached to a pedestrian. The PMM will be validated using real MoCap scenarios and will enable Spirent to increase their product offering in the area of simulation-based testing of positioning sensors for pedestrian applications by generating human motion profiles which affect realistically the performance of GNSS user equipment

Radar and RGB-depth sensors for fall detection: a review

This paper reviews recent works in the literature on the use of systems based on radar and RGB-Depth (RGB-D) sensors for fall detection, and discusses outstanding research challenges and trends related to this research field. Systems to detect reliably fall events and promptly alert carers and first responders have gained significant interest in the past few years in order to address the societal issue of an increasing number of elderly people living alone, with the associated risk of them falling and the consequences in terms of health treatments, reduced well-being, and costs. The interest in radar and RGB-D sensors is related to their capability to enable contactless and non-intrusive monitoring, which is an advantage for practical deployment and users’ acceptance and compliance, compared with other sensor technologies, such as video-cameras, or wearables. Furthermore, the possibility of combining and fusing information from The heterogeneous types of sensors is expected to improve the overall performance of practical fall detection systems. Researchers from different fields can benefit from multidisciplinary knowledge and awareness of the latest developments in radar and RGB-D sensors that this paper is discussing