Snake robot shape sensing using micro-inertial sensors

Real-time shape sensing and state acquisition is important for closed-loop control of hyper-redundant snake robots in minimally invasive surgery. Due to the miniaturized size of such minimally invasive surgery robots, it is not feasible to use existing angular sensors involving rotary encoders. With recent advances of the MEMS technology, micro inertial sensors have shown their potential for robot state estimation. Previous studies have demonstrated that accurate joint angles can be estimated for one degree-of-freedom (DoF) joints. However, higher DoF joints of the robot can impose a number of challenges to the current joint angle estimation methods. This paper presents a micro-sensing platform and shape reconstruction algorithm for minimally invasive surgery snake robot with two DoF joints. The method incorporates both gravitational and gyroscopic sensing for calculating the rotation difference between any consecutive robot segments. The gyroscope measurements are first used as the input to predict the rotation difference by direct orientation integration. The orientation difference is then derived from the consecutive acceleration vectors to update the prediction through a complementary filter. To demonstrate the performance of our proposed approach, a robot prototype with two universal joints was fabricated. Detailed experimental results have demonstrated that high accuracy can be achieved by using the proposed method for joint angle estimation.