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

Hong, Young-Dae

doi:10.1177/0142331221989512

Cited by 4 publications

(2 citation statements)

References 31 publications

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“…Some countries have successfully conducted deep space detection since the 21st century (Bernardini and Rinaldo, 2022; Turan et al, 2022). Deep space exploration activities can effectively promote the development and application of space technology (Song et al, 2022; Wu et al, 2012), providing a new window for understanding the evolution of the universe (He et al, 2022; Lee and Balint, 2022) with significant scientific value and strategic significance (Hong, 2021; Sullivan et al, 2022). However, exploration in deep space presents unprecedented challenges (Liu et al, 2022; Wei et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A reverse chain search algorithm for the resource constraint in deep space detectors

Qi,

Liu,

et al. 2023

Transactions of the Institute of Measurement and Control

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Deep space exploration activities can effectively promote the development and application of space technology, which holds significant scientific and strategic value. Detectors operating in deep space are of long mission periods and substantial distance from Earth, posing challenges in timely resource replenishment. Moreover, scheduled missions may face external uncertainties, hindering their smooth execution. Therefore, resource constraint processing strategies that possess dynamic adjustment capabilities play a crucial role in ensuring the successful execution of deep space detectors. Existing methods mainly focus on studying fixed mission sequences, and the efficiency of planning methods is not high. Specifically, the single uncertainty is only considered, and there is a lack of detection and processing mechanisms, rendering the requirements of deep space detectors inadequate. In this paper, we propose a reverse chain search algorithm, aiming to efficiently plan missions subject to resource constraints and let the mission sequence to possess a certain degree of dynamic repair capability. The results have demonstrated that the resource allocated to each mission is within the resource value range. Compared with the classic algorithm, the proposed algorithm has fewer iterations and whose maximum flow value is accurate. Meanwhile, the potential resource constraints problem during execution can be alerted with the detection and warning system. The missions that were warned are repaired by a dynamic resource repair system, and the proposed algorithm is of higher efficiency and a certain ability to resist external uncertainties. Overall, this paper lays a solid foundation for the processing of resource constraints for deep space detectors.

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Section: Introductionmentioning

confidence: 99%

A reverse chain search algorithm for the resource constraint in deep space detectors

Qi,

Liu,

et al. 2023

Transactions of the Institute of Measurement and Control

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show abstract

“…Currently, Hybrid Zero Dynamics (HZD) [ 1 , 2 , 3 ], Reinforce Learning (RL) [ 4 , 5 , 6 , 7 ] and Trajectory Optimization (TO) [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ] are the three mainstream methods for the biped gait planning. Because of the natural ability to deal with multifarious constraints, the TO method is particularly suitable for much more complex constraints in biped gait planning [ 10 , 12 ]. At the moment, flat terrain gait planning based on TO has produced a number of promising experimental results.…”

Section: Introductionmentioning

confidence: 99%

A Non-Flat Terrain Biped Gait Planner Based on DIRCON

et al. 2022

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Various constraints exist in bipedal movement. Due to the natural ability of effectively handling constraints, trajectory optimization has become one of the mainstream methods in biped gait planning, especially when constraints become much more complex on non-flat terrain. In this paper, we propose a multi-modal biped gait planner based on DIRCON, which can generate different gaits for multiple, non-flat terrains. Firstly, a virtual knot is designed to model the state transitions when the swing foot contacts terrain and is inserted as the first knot of the target trajectory of the current support phase. Thus, a complete gait or multi-modal gaits sequence can be generated at one time. Then, slacked complementary constraints, which can avoid undesired trajectories, are elaborated to describe the coupling relationships between terrain information and bipedal motion for trajectory optimization based gait planning. The concrete form of the gait planner is also delivered. Finally, we verify the performance of the planner, as well as the structural design of our newly designed biped robot in CoppeliaSim through flat terrain walking, stairs terrain walking and quincuncial piles walking. The three experiments show that the gaits planned by the proposed planner can enable the robot to walk stably over non-flat terrains, even through simple PD control.

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Dynamic Bipedal Walking Using Real-Time Optimization of Center of Mass Motion and Capture Point-Based Stability Controller

Kim

Hong

2021

J Intell Robot Syst

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

Cited by 4 publications

References 31 publications

A reverse chain search algorithm for the resource constraint in deep space detectors

A reverse chain search algorithm for the resource constraint in deep space detectors

A Non-Flat Terrain Biped Gait Planner Based on DIRCON

Dynamic Bipedal Walking Using Real-Time Optimization of Center of Mass Motion and Capture Point-Based Stability Controller

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