Nonlinear model predictive control for robust bipedal locomotion: exploring angular momentum and CoM height changes

Ding, Jiatao; Zhou, Chengxu; Xin, Songyan; Xiao, Xiaohui; Tsagarakis, Nikos G.

doi:10.1080/01691864.2021.1928543

Cited by 10 publications

(12 citation statements)

References 35 publications

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“…To realise balance control under dynamic disturbances, Ding et al. [52] expanded to a non‐linear MPC method for considering the CoM height fluctuation, footstep adjustment and angular momentum regulation, which demonstrates the improvement of balance ability for push recovery. Daneshmand et al.…”

Section: Model‐based Gait Control Methodsmentioning

confidence: 99%

An overview on bipedal gait control methods

Hu,

Xie,

Gao

et al. 2023

IET Collab Intel Manufact

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Bipedal gait control has always been a very challenging issue due to the multi‐joint and non‐linear structure of humanoid robots and frequent robot–environment interactions. To realise stable and robust bipedal walking, many aspects including robot modelling, gait stability and environmental adaptivity should be considered to design the gait control method. In this paper, a general description of bipedal gait and the corresponding evaluation indicators are introduced. Moreover, the existing bipedal gait control methods are classified into model‐based gait, stability criterion‐based gait and learning strategy‐based gait and a comprehensive review is conducted. Finally, the existing challenges and development trends of bipedal gait control are presented.

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Section: Model‐based Gait Control Methodsmentioning

confidence: 99%

An overview on bipedal gait control methods

Hu,

Xie,

Gao

et al. 2023

IET Collab Intel Manufact

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“…Remark 2: Due to the utilization of CoP constraints (4), the above QCQP is a nonconvex problem. Although it can be solved efficiently by SQP, as done in [14], [18], and [19], the global convergence is not guaranteed. Here, we resort to the SDR technique to attain the global optimum, see Appendix A.…”

Section: C) Constraints On Com Motionmentioning

confidence: 99%

“…Although the authors in [16] combined ankle, stepping, and hip strategies, they ignored height variation To integrate ankle, stepping, hip, and height variation strategies in a unified way, the authors in [17] proposed an LMPC approach where the height trajectory was defined in advance. To alleviate this limitation, [18] proposed an NMPC scheme, which was formulated as a nonconvex quadratically constrained quadratic programming (QCQP) problem. And an enhanced version could be found in [19].…”

Section: Introductionmentioning

confidence: 99%

“…And an enhanced version could be found in [19]. Although the nonconvex QCQP could be solved efficiently by sequential quadratic programming (SQP), the global convergence was hardly guaranteed in [18] and [19].…”

Section: Introductionmentioning

confidence: 99%

“…In the presence of dynamic disturbances, including modeling errors such as those caused by the usage of a simplified dynamic model (e.g., the LIP model [1]- [3], [20]) and external perturbations such as those caused by external forces, estimating robot states is a nontrivial problem, especially when considering the height variation and the change of angular momentum. To reduce modeling errors, the VHIP model is adopted to account for the height variation (e.g., [14], [21]- [23]) and the IPF model is proposed for characterizing the angular momentum adaptation (e.g., [15], [18], and [24]). Recently, multimass models, such as three-mass LIP [25], [26], have been used to compensate for the mass distribution.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust Locomotion Exploiting Multiple Balance Strategies: An Observer-Based Cascaded Model Predictive Control Approach

Ding

Han

et al. 2022

IEEE/ASME Trans. Mechatron.

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Robust locomotion is a challenging task for humanoid robots, especially when considering dynamic disturbances. This article proposes a disturbance observer-based cascaded model predictive control (MPC) approach for bipedal locomotion, with the capability of exploiting ankle, stepping, hip and height variation strategies. Specifically, based on the variable-height inverted pendulum model, a nonlinear MPC that is run at a low frequency is built for 3-D locomotion (i.e., with height variation) while accounting for the footstep modulation as well. Differing from previous works, the nonlinear MPC is formulated as a convex optimization problem by semidefinite relaxation. Subsequently, assuming a flywheel at the pelvis center, a linear MPC that is run at a high frequency is proposed to regulate angular momentum (e.g., through rotating the upper body), which is solved by convex quadratic programming. To run the cascaded MPC in a closed-loop manner, a high order sliding mode observer is designed to estimate system states and dynamic disturbances simultaneously. Simulation and hardware experiments demonstrate the walking robustness in real-world scenarios, including 3-D walking with varying speeds, walking across non-coplanar terrains and push recovery.

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Humanoid Robot Motion Planning Approaches: a Survey

de Lima,

Khan,

Tufail

et al. 2024

J Intell Robot Syst

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Humanoid robots are complex, dynamic systems. Any humanoid robotic application starts with determining a sequence of optimal paths to perform a given task in a known or unknown environment. This paper critically reviews and rates available literature on the three key areas of multi-level motion and task planning for humanoid robots. First is efficiency while navigating and manipulating objects in environments designed for humans. Here, the research has broadly been summarized as behavior cloning approaches. Second is robustness to perturbations and collisions caused by operation in dynamic and unpredictable environments. Here, the modeling approaches integrated into motion planning algorithms have been the focus of many researchers studying humanoid motion’s balance and dynamic stability aspects. Last is real-time performance, wherein the robot must adjust its motion based on the most recent sensory data to achieve the required degree of interaction and responsiveness. Here, the focus has been on the kinematic constraints imposed by the robot’s mechanical structure and joint movements. The iterative nature of solving constrained optimization problems, the computational complexity of forward and inverse kinematics, and the requirement to adjust to a rapidly changing environment all pose challenges to real-time performance. The study has identified current trends and, more importantly, research gaps while pointing to areas needing further investigation.

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Nonlinear model predictive control for robust bipedal locomotion: exploring angular momentum and CoM height changes

Cited by 10 publications

References 35 publications

An overview on bipedal gait control methods

An overview on bipedal gait control methods

Robust Locomotion Exploiting Multiple Balance Strategies: An Observer-Based Cascaded Model Predictive Control Approach

Humanoid Robot Motion Planning Approaches: a Survey

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