A synergistic approach to the Real-Time estimation of the feet ground reaction forces and centers of pressure in humans with application to Human-Robot collaboration

This letter proposes a novel technique for the realtime estimation of the human feet ground reaction forces (GREs) and centers of pressure (CoP) from the whole-body CoP and body configuration. The estimated variables are used for the estimation of the overloading torques in human joints during double support, with the aim to provide an evaluation of the human ergonomics while performing heavy manipulation tasks with a robot, or when exposed to an external force. The estimation of the feet GREs and CoP is achieved using a synergistic approach that combines a simplified geometrical model of the whole-body CoP and a learning technique to address the underdetermined force distribution problem. First, a statically equivalent serial chain (SESC) model which enables the whole-body CoP estimation is identified. Then, the estimated whole-body CoP and the simplified body pose information are used for the training and validation of the learning technique. The displacements between the feet CoP estimated using the synergistic model and the values measured using insole sensors, along with the GRFs vectors are finally used for the estimation of the body overloading joint torques. The proposed synergistic model is first validated experimentally in five subjects. Next, its real-time efficacy is assessed in a human robot load sharing task, in which the robot trajectories are optimized to minimize the effect of the external load on the human joints.