Search Results for author:
Found 5 papers, 0 papers with code
Automated Feature Selection for Inverse Reinforcement Learning
Inverse reinforcement learning (IRL) is an imitation learning approach to learning reward functions from expert demonstrations.
The Role of Higher-Order Cognitive Models in Active Learning
Building machines capable of efficiently collaborating with humans has been a longstanding goal in artificial intelligence.
Benchmarking the Sim-to-Real Gap in Cloth Manipulation
The dataset is collected by performing a dynamic as well as a quasi-static cloth manipulation task involving contact with a rigid table.
QDP: Learning to Sequentially Optimise Quasi-Static and Dynamic Manipulation Primitives for Robotic Cloth Manipulation
To address this challenge, we introduce the Quasi-Dynamic Parameterisable (QDP) method, which optimises parameters such as the motion velocity in addition to the pick and place positions of quasi-static and dynamic manipulation primitives.
Trajectory Optimization on Matrix Lie Groups with Differential Dynamic Programming and Nonlinear Constraints
Matrix Lie groups are an important class of manifolds commonly used in control and robotics, and the optimization of control policies on these manifolds is a fundamental problem.
