Push recovery control for the underactuated lower extremity exoskeleton based on improved capture point concept

Purpose The purpose of this paper is to use a simple method to enhance the ability of lower limb exoskeletons to restore balance under large interference conditions and to solve the problem that biped robot stability criterion cannot be fully applied to the underactuated lower limb exoskeletons. Design/methodology/approach The method used in this paper is to construct an underactuated lower extremity exoskeleton ankle joint with a torsion spring. Based on the constructed exoskeleton, the linear inverted torsion spring pendulum model is proposed, and the traditional capture point (CP) concept is optimized. Findings The underactuated exoskeleton ankle joint with torsion springs, combined with the improved CP concept, can effectively reduce the forward stepping distance under the same interference condition, which is equivalent to enhancing the balance ability of the lower extremity exoskeleton. Originality/value The contribution of this paper is to enhance the balance ability of the exoskeleton of the lower limbs under large interference conditions. The torsion spring is used as the exoskeleton ankle joint, and the traditional CP concept is optimized according to the constructed exoskeleton.

Balance Recovery based on Whole-Body Control using Joint Torque Feedback for Quadrupedal Robots

In legged locomotion, the contact force between a robot and the ground plays a crucial role in balancing the robot. However, in quadrupedal robots, general whole-body controllers generate feed-forward force commands without considering the actual torque or force feedback. This paper presents a whole-body controller by using the actual joint torque measured from a torque sensor, which enables the quadrupedal robot to demonstrate both dynamic locomotion and reaction to external disturbances. We compute external joint torque using the measured joint torque and the robot's dynamics, and then transform this to the moment of the center of mass (CoM). Using the computed CoM moment, the moment-based impedance controller distributes a feed-forward force corresponding to the desired moment of the CoM to stabilize the robot's balance. Furthermore, to recover balance, the CoM motion is generated using capture point-based stepping control and zero moment point trajectory. The proposed whole-body controller was tested on a quadrupedal robot, named AiDIN-VI. Locomotive abilities on uneven terrains and slopes and in the presence of external disturbances are verified through experiments.

Extraction of Guardrails from MMS Data Using Convolutional Neural Network

Mobile mapping systems can capture point clouds and digital images of roadside objects. Such data are useful for maintenance, asset management, and 3D map creation. In this paper, we discuss methods for extracting guardrails that separate roadways and walkways. Since there are various shape patterns for guardrails in Japan, flexible methods are required for extracting them. We propose a new extraction method based on point processing and a convolutional neural network (CNN). In our method, point clouds and images are segmented into small fragments, and their features are extracted using CNNs for images and point clouds. Then, features from images and point clouds are combined and investigated using whether they are guardrails or not. Based on our experiments, our method could extract guardrails from point clouds with a high success rate.

Biomechanics of Single Stair Climb with Implications for Inverted Pendulum Modeling

Step-by-step (SBS) stair navigation is used by those with movement limitations or lower-limb prosthetics, and by humanoid robots. Knowledge of biomechanical parameters for SBS gait, however, is limited. Inverted pendulum (IP) models used to assess dynamic stability have not been applied to SBS gait. This study examined the ability of the linear inverted pendulum (LIP) model and a closed-form, variable-height inverted pendulum (VHIP) model to predict capture point stability in healthy adults executing a single stair climb. A second goal was to provide baseline kinematic and kinetic data for SBS gait. Twenty young adults executed a single step onto stairs of two heights while attached marker positions and ground reaction forces were recorded. OpenSim software determined body kinematics and joint kinetics. Trials were analyzed with LIP and VHIP models, and the predicted capture point compared to the actual center-of-pressure on the stair. Lower-limb joint moments were larger than those reported for step-over-step stair gait. Leading knee rather than trailing ankle was dominant. Center-of-mass (CoM) velocity peaked at push-off. The VHIP model accounted for only slightly more than half of the forward progression of the vertical projection of the CoM, and was not better than LIP predictions. This suggests that IP models are limited in modeling SBS gait, likely due to large hip and knee moments. The results from this study may also provide target values and strategies to aid design of lower-limb prostheses and powered exoskeletons.

Real-time footstep planning including capture point trajectory optimization for stable biped navigation

For stable and efficient biped navigation, a real-time footstep planner taking bipedal dynamics for walking stability control into consideration is proposed. A capture point (CP)-based walking controller is utilized, and footstep planning including reference CP trajectory generation is formulated as an optimization problem. The footstep planning problem is solved using a particle swarm optimization algorithm. The walking period at every footstep is also planned to achieve more effective footstep planning, along with foot placement. Consequently, footstep placement, walking period, and reference CP trajectory for each footstep are optimized by the proposed method. The footstep optimization is performed in real-time without any approximations or precomputations. The effectiveness of the proposed method is demonstrated through experiments in a three-dimensional environment.