3D Modelling of Biped Robot Locomotion with Walking Primitives Approach in Simulink Environment

Khusainov, Ramil; Shimchik, Ilya; Afanasyev, Ilya; Magid, Evgeni

doi:10.1007/978-3-319-31898-1_16

Cited by 14 publications

(8 citation statements)

References 21 publications

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“…Mass and size parameters of the robot legs are given in Table 1. The total mass of the robot is 65 kg and the height is 1442 mm; for further details about AR-601M the interested reader could refer to Khusainov et al 12 . …”

Section: Ar-601m Robot Descriptionmentioning

confidence: 99%

Bipedal robot locomotion modelling with virtual height inverted pendulum and preview control approaches in Simulink environment

Khusainov¹,

Afanasyev²,

Sabirova³

et al. 2016

JRNAL

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Control algorithms development for humanoid locomotion is difficult due to humanoid's high number of Degrees of Freedom and system nonlinearity. Moreover, a humanoid may lose balance as its walking speed changes. We present AR-601M humanoid locomotion modelling with virtual height inverted pendulum and preview control approaches. A step length and period influence on walking stability were investigated and simulated within Simulink environment. Achievable in simulation maximal torques in leg joints and corresponding trajectories were verified against attainable robot motors' values.

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Section: Ar-601m Robot Descriptionmentioning

confidence: 99%

Bipedal robot locomotion modelling with virtual height inverted pendulum and preview control approaches in Simulink environment

Khusainov¹,

Afanasyev²,

Sabirova³

et al. 2016

JRNAL

Self Cite

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“…There are many models for legged-robot locomotion. Most researchers implement trajectory-based locomotion for its simplicity; this has been done in bipedal (Manchester et al, 2011) (Zhang et al, 2014b) (Nandi et al, 2016) (Saputra et al, 2015a) (Khusainov et al, 2016) (Saputra et al, 2015c), quadrupedal (Winkler et al, 2015) (Kolter et al, 2008) (Mastalli et al, 2017) (Zhang et al, 2016) (Matsuzawa et al, 2016), and hexapodal robots (Qian and Goldman, 2015) (Zhu et al, 2016). Trajectory-based models control the motion planning in Cartesian coordinates using polynomial equations or Bézier curves (Manchester et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

AQuRo: A Cat-like Adaptive Quadruped Robot With Novel Bio-Inspired Capabilities

et al. 2021

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There are currently many quadruped robots suited to a wide range of applications, but traversing some terrains, such as vertical ladders, remains an open challenge. There is still a need to develop adaptive robots that can walk and climb efficiently. This paper presents an adaptive quadruped robot that, by mimicking feline structure, supports several novel capabilities. We design a novel paw structure and several point-cloud-based sensory structures incorporating a quad-composite time-of-flight sensor and a dual-laser range finder. The proposed robot is equipped with physical and cognitive capabilities which include: 1) a dynamic-density topological map building with attention model, 2) affordance perception using the topological map, and 3) a neural-based locomotion model. The novel capabilities show strong integration between locomotion and internal–external sensory information, enabling short-term adaptations in response to environmental changes. The robot performed well in several situations: walking on natural terrain, walking with a leg malfunction, avoiding a sudden obstacle, climbing a vertical ladder. Further, we consider current problems and future development.

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“…In this way, as robot manipulators, the biped foot support can be considered a successive open loop of kinematic chain from the support point to the free ends. There have been some recent three-dimensional model improvements to the two-dimensional biped robot models (Grizzle et al, 2010;Khusainov et al, 2016;Bailly et al, 2021). However, they are still not sophisticated compared with a real human body.…”

Section: Introductionmentioning

confidence: 99%

Computational Modeling: Human Dynamic Model

2021

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Improvements in quantitative measurements of human physical activity are proving extraordinarily useful for studying the underlying musculoskeletal system. Dynamic models of human movement support clinical efforts to analyze, rehabilitate injuries. They are also used in biomechanics to understand and diagnose motor pathologies, find new motor strategies that decrease the risk of injury, and predict potential problems from a particular procedure. In addition, they provide valuable constraints for understanding neural circuits. This paper describes a physics-based movement analysis method for analyzing and simulating bipedal humanoid movements. The model includes the major body segments and joints to report human movements' energetic components. Its 48 degrees of freedom strike a balance between very detailed models that include muscle models and straightforward two-dimensional models. It has sufficient accuracy to analyze and synthesize movements captured in real-time interactive applications, such as psychophysics experiments using virtual reality or human-in-the-loop teleoperation of a simulated robotic system. The dynamic model is fast and robust while still providing results sufficiently accurate to be used to animate a humanoid character. It can also estimate internal joint forces used during a movement to create effort-contingent stimuli and support controlled experiments to measure the dynamics generating human behaviors systematically. The paper describes the innovative features that allow the model to integrate its dynamic equations accurately and illustrates its performance and accuracy with demonstrations. The model has a two-foot stance ability, capable of generating results comparable with an experiment done with subjects, and illustrates the uncontrolled manifold concept. Additionally, the model's facility to capture large energetic databases opens new possibilities for theorizing as to human movement function. The model is freely available.

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3D Modelling of Biped Robot Locomotion with Walking Primitives Approach in Simulink Environment

Cited by 14 publications

References 21 publications

Bipedal robot locomotion modelling with virtual height inverted pendulum and preview control approaches in Simulink environment

Bipedal robot locomotion modelling with virtual height inverted pendulum and preview control approaches in Simulink environment

AQuRo: A Cat-like Adaptive Quadruped Robot With Novel Bio-Inspired Capabilities

Computational Modeling: Human Dynamic Model

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