Optimization based controller design and implementation for the Atlas robot in the DARPA Robotics Challenge Finals

This paper is about improving joint and actuator velocity estimates on a human-sized hydraulic humanoid robot by adding a network of inexpensive microelectromechanical systems (MEMS) gyroscopes. Due to the lack of joint velocity sensors on the majority of humanoid robots, the joint velocity estimates often become a limiting factor on the controller performance. The distributed gyroscopes serve as indirect sensors of the joint velocities that can be estimated by a Kalman filter. Using this framework, we achieve higher velocity gains at the center of mass level on an Atlas hydraulic humanoid robot, which translates into better control performance.

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“…Details about our controller can be found in [11] [12]. Essentially, we track the desired Center of Mass (CoM) trajectory in the following waÿ…”

Section: Controllermentioning

confidence: 99%

A distributed MEMS gyro network for joint velocity estimation

Xinjilefu

Feng

Atkeson

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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“…where the gain matrices are positive definite,ẋ * is the output of the ZMP-CoM (17) controller and x * is the integrated signal. Finally, an inequality constraint is added to limit the maximum joint velocities.…”

Section: Kinematics Based Whole-body Qp Control Layermentioning

confidence: 99%

A Benchmarking of DCM-Based Architectures for Position, Velocity and Torque-Controlled Humanoid Robots

Romualdi

Dafarra

et al. 2020

Int. J. Human. Robot.

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This paper contributes towards the benchmarking of control architectures for bipedal robot locomotion. It considers architectures that are based on the Divergent Component of Motion (DCM) and composed of three main layers: trajectory optimization, simplified model control, and whole-body QP control layer. While the first two layers use simplified robot models, the whole-body QP control layer uses a complete robot model to produce either desired positions, velocities, or torques inputs at the joint-level. This paper then compares two implementations of the simplified model control layer, which are tested with position, velocity, and torque control modes for the whole-body QP control layer. In particular, both an instantaneous and a Receding Horizon controller are presented for the simplified model control layer. We show also that one of the proposed architectures allows the humanoid robot iCub to achieve a forward walking velocity of 0.3372 meters per second, which is the highest walking velocity achieved by the iCub robot.

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“…The batteries are housed inside the base, and a computer mount and WiFi router sit on the base [Color figure can be viewed at wileyonlinelibrary.com] with wheels on the legs, allowing it to walk or drive through the outdoor terrain (Wang, Zheng, Jun, & Oh, 2014). The Atlas was developed as a high powered humanoid using hydraulic actuators to be used as a standard platform for DRC (Feng, Xinjilefu, Atkeson, & Kim, 2015). The RoboSimian was a four-legged robot that can walk with a one-leg or twoleg swing gait (Byl & Byl, 2015).…”

Section: Related Workmentioning

confidence: 99%

Multimodal sensing and active continuous closed‐loop feedback for achieving reliable manipulation in the outdoor physical world

Chan¹,

Mizohana²,

Chen³

et al. 2018

Journal of Field Robotics

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The use of field robots can greatly decrease the amount of time, effort, and associated risk compared to if human workers were to carryout certain tasks such as disaster response. However, transportability and reliability remain two main issues for most current robot systems. To address the issue of transportability, we have developed a lightweight modularizable platform named AeroArm. To address the issue of reliability, we utilize a multimodal sensing approach, combining the use of multiple sensors and sensor types, and the use of different detection algorithms, as well as active continuous closed‐loop feedback to accurately estimate the state of the robot with respect to the environment. We used Challenge 2 of the 2017 Mohammed Bin Zayed International Robotics Competition as an example outdoor manipulation task, demonstrating the capabilities of our robot system and approach in achieving reliable performance in the fields, and ranked fifth place internationally in the competition.

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Optimization based controller design and implementation for the Atlas robot in the DARPA Robotics Challenge Finals

Cited by 93 publications

References 23 publications

A distributed MEMS gyro network for joint velocity estimation

A distributed MEMS gyro network for joint velocity estimation

A Benchmarking of DCM-Based Architectures for Position, Velocity and Torque-Controlled Humanoid Robots

Multimodal sensing and active continuous closed‐loop feedback for achieving reliable manipulation in the outdoor physical world

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