Design and adaptive balance control of a biped robot with fewer actuators for slope walking

Ito, Satoshi; Nishio, Satoshi; Ino, Masaaki; Morita, Ryosuke; Matsushita, Kojiro; Sasaki, Minoru

doi:10.1016/j.mechatronics.2017.11.007

Cited by 25 publications

(3 citation statements)

References 11 publications

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“…The method is tested using simulation and experiment. Recently, control techniques have been applied to balance a biped robot while walking in slopes [14], along with the use of central pattern generation [15,16].…”

Section: Classical Approachesmentioning

confidence: 99%

Learning an Efficient Gait Cycle of a Biped Robot Based on Reinforcement Learning and Artificial Neural Networks

Morales¹,

Rufino²

2019

Applied Sciences

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Programming robots for performing different activities requires calculating sequences of values of their joints by taking into account many factors, such as stability and efficiency, at the same time. Particularly for walking, state of the art techniques to approximate these sequences are based on reinforcement learning (RL). In this work we propose a multi-level system, where the same RL method is used first to learn the configuration of robot joints (poses) that allow it to stand with stability, and then in the second level, we find the sequence of poses that let it reach the furthest distance in the shortest time, while avoiding falling down and keeping a straight path. In order to evaluate this, we focus on measuring the time it takes for the robot to travel a certain distance. To our knowledge, this is the first work focusing both on speed and precision of the trajectory at the same time. We implement our model in a simulated environment using q-learning. We compare with the built-in walking modes of an NAO robot by improving normal-speed and enhancing robustness in fast-speed. The proposed model can be extended to other tasks and is independent of a particular robot model.

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Section: Classical Approachesmentioning

confidence: 99%

Learning an Efficient Gait Cycle of a Biped Robot Based on Reinforcement Learning and Artificial Neural Networks

Morales¹,

Rufino²

2019

Applied Sciences

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“…Asimo (IEEE Spectrum: Technology, Engineering, and Science News, 2018) is a humanoid robot developed by Honda with bipedal walking technology for motion. Even though, there are researches (Azeta et al, 2018, Choudhury et al, 2018, Ito et al, 2018, Xiang et al, 2015 focusing on the development of the mobility replicating human motion, humanoid robots with omni wheels provide efficient mobility. Pepper robot (Pandey & Gelin, 2018) is a humanoid designed and developed with omni wheels for motion.…”

Section: Introductionmentioning

confidence: 99%

Low Cost Collision Avoidance System on Holonomic and Non- Holonomic Mobile Robots

Ravendran

Hsu

2019

mijst

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Technological advancement in industries necessitates development in autonomous mobile robots with obstacle avoidance for applications in industries, hospitals and educational environment.Holonomic motion allows the mobile robots to move instantaneously in any direction with no constraints while non-holonomic motion restricts the motion in limited directions. This study presents the comparison of obstacle avoidance performance using low cost sensors on holonomic and non-holonomic mobile robots. The robot prototypes are developed and implemented with stable control system for better mobility. Experimental results show that the omnidirectional mobile robots avoid collisions with limited space and less time while nonholonomic mobile platforms exhibits reduced computational complexity and efficient implementation. The developed mobile robots can be used for diverse task specification applications.

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“…Similarly, Ito et al 28 proposed an actuation mechanism for a biped robot that reduced the number of actuators in the hip joint structure without sacrificing the ability to walk adaptively on slopes. An inertial measurement unit, accelerometer, and a gyroscope have often been placed in the robot's chest to measure the body's tilt posture on uneven terrains.…”

Section: Introductionmentioning

confidence: 99%

Posture control for humanoid robot on uneven ground and slopes using inertial sensors

Chiang

Wang

2014

Advances in Mechanical Engineering

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We designed a stable gait pattern and posture-control balance system to enable a biped humanoid robot to maintain balance and avoid falling when walking on uneven ground or slopes. In this study, we first examined the problem of gait generation and the balance of a humanoid robot and then proposed a posture-control balance system using the inertial sensors of a gyroscope and accelerometer to sense the tilt angle of the robot according to the environment. To process the data obtained by the sensors, the mean filter was applied to eliminate the noise in the data, and the complementary filter was used to properly combine the data from both the gyroscope and accelerometer. The system further modifies the gait and posture of the robot based on the results obtained through a fuzzy system to attain the angle of balance and stabilization. A robot with an open platform was used to test the implementation of the proposed algorithm, and the experimental results demonstrated that the robot could successfully maintain balance when walking uphill and downhill on uneven surfaces. Moreover, because only one parameter needs to be adjusted when applying the balance-control system, the system can be easily extended to any related humanoid robot.

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Design and adaptive balance control of a biped robot with fewer actuators for slope walking

Cited by 25 publications

References 11 publications

Learning an Efficient Gait Cycle of a Biped Robot Based on Reinforcement Learning and Artificial Neural Networks

Learning an Efficient Gait Cycle of a Biped Robot Based on Reinforcement Learning and Artificial Neural Networks

Low Cost Collision Avoidance System on Holonomic and Non- Holonomic Mobile Robots

Posture control for humanoid robot on uneven ground and slopes using inertial sensors

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