Development of a dynamics model for the Baxter robot

Smith, Alex; Yang, Chenguang; Li, Chunxu; Ma, Hongbin; Zhao, Lina

doi:10.1109/icma.2016.7558740

Cited by 16 publications

(8 citation statements)

References 10 publications

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“…In this section, the validity of the proposed method is further verified by experiments on a robotic platform Sawyer, which has been developed by Rethink Robotics [20]. The experimental scenario is shown in Fig.…”

Section: Methodsmentioning

confidence: 85%

Waypoints updating based on Adam and ILC for path learning in physical human-robot interaction

Xia

Song

Huang

et al. 2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

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This paper presents a novel method for learning and tracking of the desired path of the human partner in physical human-robot interaction. Combining the Adam optimization algorithm with iteration learning control (ILC), a path learning method is designed to generate and update reference waypoints according to the human partner's desired path. This method firstly uses the Adam optimization algorithm to update the robot's reference waypoints in an online manner. Then, an ILC is developed to further modify the waypoints and reduce the difference between the robot's actual path and the human partner's desired path in an iterative manner. Simulations and experiments on a 7-DOF Sawyer robot are carried out to show the effectiveness of our proposed method.

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Section: Methodsmentioning

confidence: 85%

Waypoints updating based on Adam and ILC for path learning in physical human-robot interaction

Xia

Song

Huang

et al. 2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

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“…In this section, the validity of our proposed method is further verified by experiments with a robotic platform Baxter, which has been developed by Rethink Robotics [40] (see Fig. 8).…”

Section: Comparison With Impedance Controlmentioning

confidence: 81%

A Proactive Controller for Human-Driven Robots Based on Force/Motion Observer Mechanisms

Yang

Huang

et al. 2022

IEEE Trans. Syst. Man Cybern, Syst.

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“…The Baxter robot has two arms and each of the Baxter robot has 7 Degrees of Freedom (DOF): shoulder joints s 0 , s 1 , elbow joints: e 0 , e 1 and wrist joints: w 0 , w 1 and w 2 . The model of the Baxter is introduced in [38]. In this experiment, at the beginning, when there is no interaction with the external environment, the robot manipulator will follow the desired trajectory.…”

Section: Experiments Resultsmentioning

confidence: 99%

“…In this paper, we use the model of Baxter robot in [38]. As we can see, combine (21) with (23) and define r = K p e p , we can obtainṙ…”

Section: A Observer Based On the Generalized Momentummentioning

confidence: 99%

Force Sensorless Admittance Control With Neural Learning for Robots With Actuator Saturation

Peng

Yang

et al. 2020

IEEE Trans. Ind. Electron.

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157

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In this paper, we present a sensorless admittance control scheme for robotic manipulators to interact with unknown environments in the presence of actuator saturation. The external environment are defined as linear models with unknown dynamics. Using admittance control, the robotic manipulator is controlled to be compliant to external torque from the environment. The external torque acted on the end-effector is estimated by using a disturbance observer based on generalized momentum. The model uncertainties are solved by using radial basis neural networks. To guarantee the tracking performance and tackle the effect of actuator saturation, an adaptive neural network (NN) controller integrating an auxiliary system is designed to handle the actuator saturation is proposed. By employing Lyapunov stability theory, the stability of the closed-loop system is achieved. The experiments on Baxter robot are implemented to verify the the effectiveness of the proposed method.

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Development of a dynamics model for the Baxter robot

Cited by 16 publications

References 10 publications

Waypoints updating based on Adam and ILC for path learning in physical human-robot interaction

Waypoints updating based on Adam and ILC for path learning in physical human-robot interaction

A Proactive Controller for Human-Driven Robots Based on Force/Motion Observer Mechanisms

Force Sensorless Admittance Control With Neural Learning for Robots With Actuator Saturation

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