Ragesh Kumar Ramachandran — accepted AI-conference papers

2021

Sampling-Based Motion Planning on Sequenced Manifolds

Peter Englert, Isabel M Rayas Fernández, Ragesh Kumar Ramachandran, Gaurav Sukhatme

RSS 2021poster

We address the problem of planning robot motions in constrained configuration spaces where the constraints change throughout the motion. The problem is formulated as a fixed sequence of intersecting manifolds; which the robot needs to traverse in order to solve the task. We specify a class of sequen…

Cited by 18 Source ↗PDF ↗code ↗Scholar ↗

2020

Learning Equality Constraints for Motion Planning on Manifolds

Giovanni Sutanto, Isabel Rayas Fernández, Peter Englert, Ragesh Kumar Ramachandran, Gaurav Sukhatme

CoRL 2020

Constrained robot motion planning is a widely used technique to solve complex robot tasks. We consider the problem of learning representations of constraints from demonstrations with a deep neural network, which we call Equality Constraint Manifold Neural Network (ECoMaNN). The key idea is to learn

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗