TY - JOUR
T1 - Vertical ground reaction forces for given human standing posture with uneven terrains
T2 - Prediction and validation
AU - Yang, James
AU - Howard, Bradley
AU - Cloutier, Aimee
AU - Domire, Zachary J.
PY - 2013/3
Y1 - 2013/3
N2 - Ground reaction forces (GRFs) on individual support vary with posture and motion for bipedal mechanisms or systems due to the redundancy in the system. In digital human modeling, specifically posture prediction, the GRFs are predicted, as they are unknown in a virtual environment. Traditionally, models in which the GRFs are predicted have been presented; however, they are always assumed to be on flat ground. Little work has been done to predict the GRFs on uneven or arbitrary terrain. This paper presents a generic method to calculate the vertical GRFs for given standing postures with uneven terrain. The vertical GRFs are predicted based on the generalized forces (torque in revolute joints; force in prismatic joints) calculated using the recursive Lagrangian formulation and a 3-D zero moment point. Motion capture experiments were used to obtain postures for common standing reaching tasks. Force plates were employed to record GRF information for each task. Experimental postures were reconstructed, and the GRF prediction algorithm was used to predict the associated vertical GRFs for each task. Experimental and predicted vertical GRFs are compared to validate the prediction model. The prediction method proved to be valid, with an overall error of 6%.
AB - Ground reaction forces (GRFs) on individual support vary with posture and motion for bipedal mechanisms or systems due to the redundancy in the system. In digital human modeling, specifically posture prediction, the GRFs are predicted, as they are unknown in a virtual environment. Traditionally, models in which the GRFs are predicted have been presented; however, they are always assumed to be on flat ground. Little work has been done to predict the GRFs on uneven or arbitrary terrain. This paper presents a generic method to calculate the vertical GRFs for given standing postures with uneven terrain. The vertical GRFs are predicted based on the generalized forces (torque in revolute joints; force in prismatic joints) calculated using the recursive Lagrangian formulation and a 3-D zero moment point. Motion capture experiments were used to obtain postures for common standing reaching tasks. Force plates were employed to record GRF information for each task. Experimental postures were reconstructed, and the GRF prediction algorithm was used to predict the associated vertical GRFs for each task. Experimental and predicted vertical GRFs are compared to validate the prediction model. The prediction method proved to be valid, with an overall error of 6%.
KW - Digital human model
KW - Ground reaction forces (GRFs)
KW - Standing posture
KW - Uneven terrain
UR - http://www.scopus.com/inward/record.url?scp=84893112231&partnerID=8YFLogxK
U2 - 10.1109/TSMC.2013.2237899
DO - 10.1109/TSMC.2013.2237899
M3 - Article
AN - SCOPUS:84893112231
SN - 2168-2291
VL - 43
SP - 225
EP - 235
JO - IEEE Transactions on Human-Machine Systems
JF - IEEE Transactions on Human-Machine Systems
IS - 2
M1 - 6461536
ER -