Search Results for author: Ross Hartley

Found 6 papers, 4 papers with code

Contact-Aided Invariant Extended Kalman Filtering for Robot State Estimation

1 code implementation19 Apr 2019 Ross Hartley, Maani Ghaffari, Ryan M. Eustice, Jessy W. Grizzle

This filter combines contact-inertial dynamics with forward kinematic corrections to estimate pose and velocity along with all current contact points.


Feedback Control of a Cassie Bipedal Robot: Walking, Standing, and Riding a Segway

1 code implementation19 Sep 2018 Yukai Gong, Ross Hartley, Xingye Da, Ayonga Hereid, Omar Harib, Jiunn-Kai Huang, Jessy Grizzle

The Cassie bipedal robot designed by Agility Robotics is providing academics a common platform for sharing and comparing algorithms for locomotion, perception, and navigation.

Robotics Optimization and Control

Rapid Trajectory Optimization Using C-FROST with Illustration on a Cassie-Series Dynamic Walking Biped

1 code implementation17 Jul 2018 Ayonga Hereid, Omar Harib, Ross Hartley, Yukai Gong, Jessy W. Grizzle

One of the big attractions of low-dimensional models for gait design has been the ability to compute solutions rapidly, whereas one of their drawbacks has been the difficulty in mapping the solutions back to the target robot.

Robotics Systems and Control

Contact-Aided Invariant Extended Kalman Filtering for Legged Robot State Estimation

2 code implementations26 May 2018 Ross Hartley, Maani Ghaffari Jadidi, Jessy W. Grizzle, Ryan M. Eustice

On the basis of the theory of invariant observer design by Barrau and Bonnabel, and in particular, the Invariant EKF (InEKF), we show that the error dynamics of the point contact-inertial system follows a log-linear autonomous differential equation; hence, the observable state variables can be rendered convergent with a domain of attraction that is independent of the system's trajectory.


Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation Using Factor Graphs

no code implementations20 Mar 2018 Ross Hartley, Maani Ghaffari Jadidi, Lu Gan, Jiunn-Kai Huang, Jessy W. Grizzle, Ryan M. Eustice

The factor graph framework is a convenient modeling technique for robotic state estimation where states are represented as nodes, and measurements are modeled as factors.


Legged Robot State-Estimation Through Combined Forward Kinematic and Preintegrated Contact Factors

no code implementations15 Dec 2017 Ross Hartley, Josh Mangelson, Lu Gan, Maani Ghaffari Jadidi, Jeffrey M. Walls, Ryan M. Eustice, Jessy W. Grizzle

We introduce forward kinematic factors and preintegrated contact factors into a factor graph framework that can be incrementally solved in real-time.


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