Terrain-Adaptive, ALIP-Based Bipedal Locomotion Controller via Model Predictive Control and Virtual Constraints

Gibson, Grant; Oluwami, Dosunmu-Ogunbi,; Gong, Yukai; Grizzle, Jessy W.

doi:10.1109/iros47612.2022.9981969

Cited by 22 publications

(5 citation statements)

References 29 publications

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“…We evaluated the performance of Kinodynamic Fabrics on a variety of whole-body control tasks both in simulation and on a physical Digit robot made by Agility Robotics. Future work will integrate the Terrain-adaptive MPC formalism of [7] into the Kinodynamic Fabrics formalism. We expect it to yield more dynamic and robust locomotion of the robot, while preserving the dynamic reactivity and bimanual manipulation capabilities.…”

Section: Discussionmentioning

confidence: 99%

Exploring Kinodynamic Fabrics for Reactive Whole-Body Control of Underactuated Humanoid Robots

Adu-Bredu¹,

Gibson²,

Grizzle³

2023

Preprint

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Section: Discussionmentioning

confidence: 99%

Exploring Kinodynamic Fabrics for Reactive Whole-Body Control of Underactuated Humanoid Robots

Adu-Bredu¹,

Gibson²,

Grizzle³

2023

Preprint

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“…Currently, the QP-based optimization method is applied to solve the bipedal state at one instant time, yet cannot provide the complete gait of one or several footsteps ahead with one optimization. The gait generation can predict future locomotion if the Model Predictive Control (MPC) scheme is introduced to the trajectory optimization [20]. The MPC provides the capability to consider the step locations as design variables of the gait optimization, thereby being able to predict the whole foot trajectory along specified time horizon [21].…”

Section: Introductionmentioning

confidence: 99%

“…Normally, the MPC is mainly adopted to solve linear or convex problems, due to its expensive computational process. For bipedal gait generation, the whole-body hybrid dynamics would not be integrated into MPC-based optimization in most studies [20][21][22]. Guo et al constructed a whole-body MPC problem via synthesizing the gait library that is optimized off-line [23].…”

Section: Introductionmentioning

confidence: 99%

Gait optimization and energy-based stability for biped locomotion using large-scale programming

et al. 2023

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This paper presents a gait optimization method to generate the locomotion pattern for biped and discuss its stability. The main contribution of this paper is a newly proposed energy-based stability criterion, which permits the dynamic stable walking and could be straight-forwardly generalized to different locomotion scenarios and biped robots. The gait optimization problem is formulated subject to the constraints of the whole-body dynamics and kinematics. The constraints are established based on the modelling of bipedal hybrid dynamical systems. Following the whole-body modelling, the system energy is acquired and then applied to create the stability criterion. The optimization objective is also established on the system energy. The gait optimization is solved by being converted to a large-scale programming problem, where the transcription accuracy is improved via the spectral method. To further reduce the dimensionality of the large-scale problem, the whole-body dynamics is re-constructed. The generalization of the optimized gait is improved by the design of feedback control. The optimization examples demonstrate that the stability criterion naturally leads to a cyclic biped locomotion, though the periodicity was not previously imposed. Two simulation cases, level ground walking and slope walking, verify the generalization of the stability criterion and feedback control. The stability analyses are carried out by investigating the motions of centre of gravity and centre of pressure. It is revealed that if the tracked speed is above 0.3 m/s or the biped accelerates/climbs the slope, the stability criterion accomplishes the dynamic stable walking, where zero moment point criterion is not strictly complied.

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“…Bipedal robots are typically conceived to achieve agilelegged locomotion over irregular terrains, and maneuver in cluttered environments [1]- [3]. To explore safely in such environments, it is critical for robots to generate quick, yet smooth responses to any changes in the obstacles, map, and environment.…”

Section: Introduction and Contributionsmentioning

confidence: 99%

Realtime Safety Control for Bipedal Robots to Avoid Multiple Obstacles via CLF-CBF Constraints

Liu¹,

Li²,

Huang³

et al. 2023

Preprint

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This paper presents a reactive planning system that allows a Cassie-series bipedal robot to avoid multiple nonoverlapping obstacles via a single, continuously differentiable control barrier function (CBF). The overall system detects an individual obstacle via a height map derived from a LiDAR point cloud and computes an elliptical outer approximation, which is then turned into a CBF. The QP-CLF-CBF formalism developed by Ames et al. is applied to ensure that safe trajectories are generated. Liveness is ensured by an analysis of induced equilibrium points that are distinct from the goal state. Safe planning in environments with multiple obstacles is demonstrated both in simulation and experimentally on the Cassie biped. THIS IS AN INITIAL DRAFTWhile the paper is not yet polished, it allows the cofirst authors to highlight their research skills while they are seeking a PhD position. The full autonomy videos are upload to our YouTube channel and the video for this particular paper can be viewed here. This draft has been approved by Huang and Grizzle.

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Terrain-Adaptive, ALIP-Based Bipedal Locomotion Controller via Model Predictive Control and Virtual Constraints

Cited by 22 publications

References 29 publications

Exploring Kinodynamic Fabrics for Reactive Whole-Body Control of Underactuated Humanoid Robots

Exploring Kinodynamic Fabrics for Reactive Whole-Body Control of Underactuated Humanoid Robots

Gait optimization and energy-based stability for biped locomotion using large-scale programming

Realtime Safety Control for Bipedal Robots to Avoid Multiple Obstacles via CLF-CBF Constraints

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