Dynamic model based ground reaction force estimation for a quadruped robot without force sensor

To satisfy the rescue tasks, a heavy-duty quadruped robot is developed recently. To guarantee the payload capability, the leg design is based on a parallel mechanism and the actuators are selected as powerful motors. Foot force sensing is very important for the gait control. Traditional foot force sensors are easy to corrupt due to the strong repeated impact from the ground. In this study, the foot force estimation method is proposed from the distributed current sensing in the motor driver. It is based on a dynamic model of the robot. To compensate unknown model parameters and frictions, an improved dynamic model based on neural networks is estimated using the system identification technique from the measured data. No extra foot force or motor torque sensors are used, and the size and weight of the robot do not increase. The experiments are conducted to verify the effectiveness.