Real-Time Short-Term Pedestrian Trajectory Prediction Based on Gait Biomechanics

Abstract

The short-term prediction of a person’s trajectory during normal walking becomes necessary in many environments shared by humans and robots. Physics-based approaches based on Newton’s laws of motion seem best suited for short-term predictions, but the intrinsic properties of human walking conflict with the foundations of the basic kinematical models compromising their performance. In this paper, we propose a short-time prediction method based on gait biomechanics for real-time applications. This method relays on a single biomechanical variable, and it has a low computational burden, turning it into a feasible solution to implement in low-cost portable devices. We evaluate its performance from an experimental benchmark where several subjects walked steadily over straight and curved paths. With this approach, the results indicate a performance good enough to be applicable to a wide range of human–robot interaction applications.

Advanced Sensors Technologies Applied in Mobile Robot

“…Modifications of the bilinear interpolation method are proposed to make it applicable to path-planning applications. In [ 15 ], a method based on gait biomechanics is presented for short-term prediction of pedestrian trajectories for real-time applications. This method relies on a single biomechanical variable and has a low computational cost, making it a viable solution for implementation in low-cost wearable devices.…”