2 code implementations • 26 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.
Robotics
1 code implementation • 7 Jul 2016 • Maani Ghaffari Jadidi, Jaime Valls Miro, Gamini Dissanayake
Our approach is built on rapidly-exploring information gathering algorithms and benefits from advantages of sampling-based optimal motion planning algorithms.
Robotics
no code implementations • 20 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.
Robotics
no code implementations • 15 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.
Robotics
