Humanoid Robot Gait Generator: Foot Steps Calculation for Trajectory Following

Garton, Horatio; Bugmann, Guido; Culverhouse, Phil F.; Roberts, Stephen; Simpson, Claire; Santana, Aashish

doi:10.1007/978-3-319-10401-0_23

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…ZMP is a widely used ground reference point for biped planning and control. However, when considering the dynamics of multi-rigid bodies, it cannot accurately calculate the trajectory of the robot’s center of mass (CoM) [ 13 , 14 ]. As we know, ZMP indicates the sum of the change of angular momentum and the change of linear momentum of the system [ 15 , 16 , 17 ], and the change of angular momentum will affect the change of linear momentum.…”

Section: Ground Reference Point and Robot Motion Analysismentioning

confidence: 99%

Uneven Terrain Walking with Linear and Angular Momentum Allocation

Piao

Leng

et al. 2023

Sensors

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Uneven terrain walking is hard to achieve for most child-size humanoid robots, as they are unable to accurately detect ground conditions. In order to reduce the demand for ground detection accuracy, a walking control framework based on centroidal momentum allocation is studied in this paper, enabling a child-size humanoid robot to walk on uneven terrain without using ground flatness information. The control framework consists of three controllers: momentum decreasing controller, posture controller, admittance controller. First, the momentum decreasing controller is used to quickly stabilize the robot after disturbance. Then, the posture controller restores the robot posture to adapt to the unknown terrain. Finally, the admittance controller aims to decrease contact impact and adapt the robot to the terrain. Note that the robot uses a mems-based inertial measurement unit (IMU) and joint position encoders to calculate centroidal momentum and use force-sensitive resistors (FSR) on the robot foot to perform admittance control. None of these is a high-cost component. Experiments are conducted to test the proposed framework, including standing posture balancing, structured non-flat ground walking, and soft uneven terrain walking, with a speed of 2.8 s per step, showing the effectiveness of the momentum allocation method.

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Section: Ground Reference Point and Robot Motion Analysismentioning

confidence: 99%

Uneven Terrain Walking with Linear and Angular Momentum Allocation

Piao

Leng

et al. 2023

Sensors

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“…In 2014, Garton detailed the use of a linear inverted pendulum (LIPM) to plan walking trajectories, enabling robots to steadily move forward, stop and restore their direction of motion. He pointed out that the use of a fixed step cycle duration reduces the complexity of mathematics and the amount of computation, thus completing the simplified process of motion planning for the bipedal robot [12]. Imanishi proposed a new bipedal gait control in 2018, which does not rely on time-defined trajectories.…”

Section: Introductionmentioning

confidence: 99%

Bipedal Robot Gait Generation Using Bessel Interpolation

Wang,

Li,

Kou

et al. 2024

Biomimetics

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This paper introduces a novel approach to bipedal robot gait generation by proposing a higher-order form through the parameter equation of first-order Bessel interpolation. The trajectory planning for the bipedal robot, specifically for stepping up or down stairs, is established based on a three-dimensional interpolation equation. The experimental prototype, Roban, is utilized for the study, and the structural sketch of a single leg is presented. The inverse kinematics expression for the leg is derived using kinematic methods. Employing a position control method, the angle information is transmitted to the robot’s joints, enabling the completion of both downstairs simulation experiments and physical experiments with the Roban prototype. The analysis of the experimental process reveals a noticeable phenomenon of hip and ankle joint tilting in the robot. This observation suggests that low-cost bipedal robots driven by servo motors exhibit low stiffness characteristics in their joints.

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Joint Torques and Velocities in a 3-mass Linear Inverted Pendulum Model of Bipedal Gait

Bugmann

2015

Towards Autonomous Robotic Systems

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Humanoid Robot Gait Generator: Foot Steps Calculation for Trajectory Following

Cited by 4 publications

References 6 publications

Uneven Terrain Walking with Linear and Angular Momentum Allocation

Uneven Terrain Walking with Linear and Angular Momentum Allocation

Bipedal Robot Gait Generation Using Bessel Interpolation

Joint Torques and Velocities in a 3-mass Linear Inverted Pendulum Model of Bipedal Gait

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