Implementation of an adaptive, model free, learning controller on the Atlas robot

Atmeh, Ghassan M.; Ranatunga, Isura; Popa, Dan O.; Subbarao, Kamesh; Lewis, Frank L.; Rowe, Patrick

doi:10.1109/acc.2014.6859431

Cited by 18 publications

(4 citation statements)

References 17 publications

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“…Therefore, in recen years, many well-known robot manufacturers have adopted technology integration to im prove the accuracy and practicality of robotic vision. For example, Atlas [141] of Boston Power adopts a vision combination of binocular and structured light + LiDAR. Unlike binocular cameras and structured light, which require algorithmic processing to output 3D data, TOF can directly output the 3D data of the target object.…”

Section: Tof (Time Of Flight)mentioning

confidence: 99%

Robot Bionic Vision Technologies: A Review

Zhang¹,

Lee

2022

Applied Sciences

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The visual organ is important for animals to obtain information and understand the outside world; however, robots cannot do so without a visual system. At present, the vision technology of artificial intelligence has achieved automation and relatively simple intelligence; however, bionic vision equipment is not as dexterous and intelligent as the human eye. At present, robots can function as smartly as human beings; however, existing reviews of robot bionic vision are still limited. Robot bionic vision has been explored in view of humans and animals’ visual principles and motion characteristics. In this study, the development history of robot bionic vision equipment and related technologies are discussed, the most representative binocular bionic and multi-eye compound eye bionic vision technologies are selected, and the existing technologies are reviewed; their prospects are discussed from the perspective of visual bionic control. This comprehensive study will serve as the most up-to-date source of information regarding developments in the field of robot bionic vision technology.

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Section: Tof (Time Of Flight)mentioning

confidence: 99%

Robot Bionic Vision Technologies: A Review

Zhang¹,

Lee

2022

Applied Sciences

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“…It is well-known that the ''Atlas Robot,'' designed by the company Boston Dynamics, has powerful material-handling ability. 35 The Atlas Robot is not categorized as a wheeled-type AGV, and instead belongs to the humanoid-type robot class. This kind of humanoid-type robot will be able to partake in further material handling with the operator in a mode of ''collaborative material handling'' after the robot reaches the indicated location and finishes location-positioning.…”

Section: Introductionmentioning

confidence: 99%

Designs of human–robot interaction using depth sensor-based hand gesture communication for smart material-handling robot operations

Ding

2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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With rapid developments in biometric recognition, a great deal of attention is being paid to robots which interact smartly with humans and communicate certain types of biometrical information. Such human–machine interaction (HMI), also well-known as human–robot interaction (HRI), will, in the future, prove an important development when it comes to automotive manufacturing applications. Currently, hand gesture recognition-based HRI designs are being practically used in various areas of automotive manufacturing, assembly lines, supply chains, and collaborative inspection. However, very few studies are focused on material-handling robot interactions combined with hand gesture communication of the operator. The current work develops a depth sensor-based dynamic hand gesture recognition scheme for continuous-time operations with material-handling robots. The proposed approach properly employs the Kinect depth sensor to extract features of Hu moment invariants from depth data, through which feature-based template match hand gesture recognition is developed. In order to construct continuous-time robot operations using dynamic hand gestures with concatenations of a series of hand gesture actions, the wake-up reminder scheme using fingertip detection calculations is established to accurately denote the starting, ending, and switching timestamps of a series of gesture actions. To be able to perform typical template match on continuous-time dynamic hand gesture recognition with the ability of real-time recognition, representative frame estimates using centroid, middle, and middle-region voting approaches are also presented and combined with template match computations. Experimental results show that, in certain continuous-time periods, the proposed complete hand gesture recognition framework can provide a smooth operation for the material-handling robot when compared with robots controlled using only extractions of full frames; presented representative frames estimated by middle-region voting will maintain fast computations and still reach the competitive recognition accuracy of 90.8%. The method proposed in this study can facilitate the smart assembly line and human–robot collaborations in automotive manufacturing.

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“…11 Based on the former, the Atlas robot developed by Boston Dynamics is capable of many motion tasks. 12,13 Hosoda from Osaka University developed a lower limb jumping mechanism composed of pneumatic bionic muscles. 14 Although hydraulic driving and pneumatic driving offer some advantages, there are still some issues to deal with.…”

Section: Introductionmentioning

confidence: 99%

Motion coordination for humanoid jumping using maximized joint power

Chen

Liao

et al. 2021

Advances in Mechanical Engineering

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Jumping capability of humanoid robots can be considered as one of the cruxes to improve the performance of future humanoid robot applications. This paper presents an optimization method on a three-linkage system to achieve a jumping behavior, which is followed by the clarification of the mathematical modeling and motor-joint model with practical factors considered. In consideration of the constraints of ZMP and the performance of the motor, the output power of the joint motors is maximized as much as possible to achieve a higher height. Finally, the optimization method is verified by the simulation and experiment. Different from other electric driven robots, which take the output power of the joint as the constraint, we maximize the output power of the joint to optimize the hopping performance of the robot. Realizing dynamic jumping of humanoid robots can also provide a solid foundation for further research on running, which can greatly enhance the environmental adaptability.

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Implementation of an adaptive, model free, learning controller on the Atlas robot

Cited by 18 publications

References 17 publications

Robot Bionic Vision Technologies: A Review

Robot Bionic Vision Technologies: A Review

Designs of human–robot interaction using depth sensor-based hand gesture communication for smart material-handling robot operations

Motion coordination for humanoid jumping using maximized joint power

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