Increase the feasible step region of biped robots through active vertical flexion and extension motions

Gao, Wei; Jia, Zhenzhong; Fu, Chenglong

doi:10.1017/s0263574716000308

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…18,19 An alternative way to WBC is employing quadratic programming, [20][21][22][23][24][25] which not only allows for inequality constraints to be represented but also endures slower computations. At the middle level, various simplified CoM dynamic models have been proposed such as the Linear Inverted Pendulum Model (LIPM), [26][27][28][29] for which the CoM height is constant and the CoM horizontal dynamics are linear. Another popular model is the spring-loaded inverted pendulum (SLIP).…”

Section: Introductionmentioning

confidence: 99%

Robust Bipedal Locomotion Based on a Hierarchical Control Structure

Luo

Ruan

et al. 2019

Robotica

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SummaryTo improve biped locomotion’s robustness to internal and external disturbances, this study proposes a hierarchical structure with three control levels. At the high level, a foothold sequence is generated so that the Center of Mass (CoM) trajectory tracks a planned path. The planning procedure is simplified by selecting the midpoint between two consecutive Center of Pressure (CoP) points as the feature point. At the middle level, a novel robust hybrid controller is devised to drive perturbed system states back to the nominal trajectory within finite cycles without chattering. The novelty lies in that the hybrid controller is not subject to linear CoM dynamic constraints. The hybrid controller consists of two sub-controllers: an oscillation controller and a smoothing controller. For the oscillation controller, the desired CoM height is specified as a sine-shaped function, avoiding a new attractive limit cycle. However, this controller results in the inevitable chattering because of discontinuities. A smoothing controller provides continuous properties and thus can inhibit the chattering problem, but has a smaller region of attraction compared with the oscillation controller. A hybrid controller merges the two controllers for a smooth transition. At the low level, the desired CoM motion is defined as tasks and embedded in a whole body operational space (WBOS) controller to compute the joint torques analytically. The novelty of the low-level controller lies in that within the WBOS framework, CoM motion is not subject to fixed CoM dynamics and thus can be generalized.

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Section: Introductionmentioning

confidence: 99%

Robust Bipedal Locomotion Based on a Hierarchical Control Structure

Luo

Ruan

et al. 2019

Robotica

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“…For a while, the ability to leverage vertical CoM motions seemed lost on the way, but recent developments showed a regain of interest for this capability [6], [7], [8]. All of them share a design choice that can be traced back to the seminal work of Pratt and Drakunov [9]: they interpolate CoM trajectories in a 2D sagittal plane for the inverted pendulum model (IPM) with fixed center of pressure.…”

Section: Introductionmentioning

confidence: 99%

Balance Control Using Both ZMP and COM Height Variations: A Convex Boundedness Approach

Caron

Mallein

2018

2018 IEEE International Conference on Robotics and Automation (ICRA)

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Developments for 3D control of the center of mass (CoM) of biped robots are currently located in two local minima: on the one hand, methods that allow CoM height variations but only work in the 2D sagittal plane; on the other hand, nonconvex direct transcriptions of centroidal dynamics that are delicate to handle. This paper presents an alternative that controls the CoM in 3D via an indirect transcription that is both low-dimensional and solvable fast enough for realtime control. The key to this development is the notion of boundedness condition, which quantifies the capturability of 3D CoM trajectories.

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“…More recently, vertical movement of this point mass has been shown to be effective in achieving a diverse range of step length as well as better push recovery behavior. 7 Many diverse techniques have been attempted to overcome the challenge of walking on uneven surfaces for biped robots. Takanishi et al 8 introduced the idea of virtual surfaces to develop walking patterns over uneven surfaces; they presented a method of trunk compensation for generating dynamically feasible trajectories.…”

Section: Introductionmentioning

confidence: 99%

Trajectory generation and step planning of a 12 DoF biped robot on uneven surface

Gupta

Dutta

2018

Robotica

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SUMMARYOne of the primary goals of biped locomotion is to generate and execute joint trajectories on a corresponding step plan that takes the robot from a start point to a goal while avoiding obstacles and consuming as little energy as possible. Past researchers have studied trajectory generation and step planning independently, mainly because optimal generation of robot gait using dynamic formulation cannot be done in real time. Also, most step-planning studies are for flat terrain guided by search heuristics. In the proposed method, a framework for generating trajectories as well as an overall step plan for navigation of a 12 degrees of freedom biped on an uneven terrain with obstacles is presented. In order to accomplish this, a dynamic model of the robot is developed and a trajectory generation program is integrated with it using gait variables. The variables are determined using a genetic algorithm based optimization program with the objective of minimizing energy consumption subject to balance and kinematic constraints of the biped. A database of these variables for various terrain angles and walking motions is used to train two neural networks, one for real-time trajectory generation and another for energy estimation. To develop a global navigation strategy, a weighted A* search is used to generate the footstep plan with energy considerations in sight. The efficacy of the approach is exhibited through simulation-based results on a variety of terrains.

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Increase the feasible step region of biped robots through active vertical flexion and extension motions

Cited by 6 publications

References 15 publications

Robust Bipedal Locomotion Based on a Hierarchical Control Structure

Robust Bipedal Locomotion Based on a Hierarchical Control Structure

Balance Control Using Both ZMP and COM Height Variations: A Convex Boundedness Approach

Trajectory generation and step planning of a 12 DoF biped robot on uneven surface

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