Swift perception of interaction forces is a crucial skill required for legged robots to ensure safe human-robot interaction and dynamic contact management.Proprioceptive-based interactive force is widely applied due t...Swift perception of interaction forces is a crucial skill required for legged robots to ensure safe human-robot interaction and dynamic contact management.Proprioceptive-based interactive force is widely applied due to its outstanding cross-platform versatility.In this paper,we present a novel interactive force observer,which possesses superior dynamic tracking performance.We propose a dynamic cutoff frequency configuration method to replace the conventional fixed cutoff frequency setting in the traditional momentum-based observer(MBO).This method achieves a balance between rapid tracking and noise suppression.Moreover,to mitigate the phase lag introduced by the low-pass filtering,we cascaded a Newton Predictor(NP)after MBO,which features simple computation and adaptability.The precision analysis of this method has been presented.We conducted extensive experiments on the point-foot biped robot BRAVER to validate the performance of the proposed algorithm in both simulation and physical prototype.展开更多
To develop sophisticated and efficient control strategies for exoskeleton devices,acquiring the information of interaction forces between the wearer and the wearable device is essential.However,obtaining the interacti...To develop sophisticated and efficient control strategies for exoskeleton devices,acquiring the information of interaction forces between the wearer and the wearable device is essential.However,obtaining the interaction force via conventional methods,such as direct measurement using force sensors,is problematic.This paper proposes a kinematic data-based estimation method to evaluate the interaction force between human lower limbs and passive exoskeleton links during level ground walking.Unlike conventional methods,the proposed method requires no force sensors and is computationally cheaper to obtain the calculation results.To obtain more accurate kinematic data,a marker refinement algorithm based on bilevel optimization framework is adopted.The interaction force is evaluated by a spring model,which is used to imitate the binding behavior between human limbs and the exoskeleton links.The deflection of the spring model is calculated based on the assumption that the phase delay between human limb and exoskeleton link can be presented by the sequence of frames of kinematic data.Experimental results of six subjects indicate that our proposed method can estimate the interaction forces during level ground walking.Moreover,a case study of bandage location optimization is conducted to demonstrate the usefulness of obtaining the interaction information.展开更多
基金supported in part by the National Key Research and Development Program of China(2022YFB4701504)the National Natural Science Foundation of China(62373223 and 62203268)Youth Innovation and Technology Support Plan for Higher Education Institutions in Shandong Province(2023KJ029).
文摘Swift perception of interaction forces is a crucial skill required for legged robots to ensure safe human-robot interaction and dynamic contact management.Proprioceptive-based interactive force is widely applied due to its outstanding cross-platform versatility.In this paper,we present a novel interactive force observer,which possesses superior dynamic tracking performance.We propose a dynamic cutoff frequency configuration method to replace the conventional fixed cutoff frequency setting in the traditional momentum-based observer(MBO).This method achieves a balance between rapid tracking and noise suppression.Moreover,to mitigate the phase lag introduced by the low-pass filtering,we cascaded a Newton Predictor(NP)after MBO,which features simple computation and adaptability.The precision analysis of this method has been presented.We conducted extensive experiments on the point-foot biped robot BRAVER to validate the performance of the proposed algorithm in both simulation and physical prototype.
基金This work was supported in part by the National Natural Science Foundation of China under grant nos.61603284 and 61903286.
文摘To develop sophisticated and efficient control strategies for exoskeleton devices,acquiring the information of interaction forces between the wearer and the wearable device is essential.However,obtaining the interaction force via conventional methods,such as direct measurement using force sensors,is problematic.This paper proposes a kinematic data-based estimation method to evaluate the interaction force between human lower limbs and passive exoskeleton links during level ground walking.Unlike conventional methods,the proposed method requires no force sensors and is computationally cheaper to obtain the calculation results.To obtain more accurate kinematic data,a marker refinement algorithm based on bilevel optimization framework is adopted.The interaction force is evaluated by a spring model,which is used to imitate the binding behavior between human limbs and the exoskeleton links.The deflection of the spring model is calculated based on the assumption that the phase delay between human limb and exoskeleton link can be presented by the sequence of frames of kinematic data.Experimental results of six subjects indicate that our proposed method can estimate the interaction forces during level ground walking.Moreover,a case study of bandage location optimization is conducted to demonstrate the usefulness of obtaining the interaction information.
