Differentiable constrained imitation learning for robot motion planning and control
Motion planning and control are crucial components of robotics applications like automated
driving. Here, spatio-temporal hard constraints like system dynamics and safety boundaries …
driving. Here, spatio-temporal hard constraints like system dynamics and safety boundaries …
No need for interactions: Robust model-based imitation learning using neural ode
Interactions with either environments or expert policies during training are needed for most
of the current imitation learning (IL) algorithms. For IL problems with no interactions, a typical …
of the current imitation learning (IL) algorithms. For IL problems with no interactions, a typical …
Improving behavioural cloning with positive unlabeled learning
Learning control policies offline from pre-recorded datasets is a promising avenue for
solving challenging real-world problems. However, available datasets are typically of mixed …
solving challenging real-world problems. However, available datasets are typically of mixed …
LeTO: Learning Constrained Visuomotor Policy with Differentiable Trajectory Optimization
Z Xu, Y She - arXiv preprint arXiv:2401.17500, 2024 - arxiv.org
This paper introduces LeTO, a method for learning constrained visuomotor policy via
differentiable trajectory optimization. Our approach uniquely integrates a differentiable …
differentiable trajectory optimization. Our approach uniquely integrates a differentiable …
Imitation learning via simultaneous optimization of policies and auxiliary trajectories
Imitation learning (IL) is a frequently used approach for data-efficient policy learning. Many
IL methods, such as Dataset Aggregation (DAgger), combat challenges like distributional …
IL methods, such as Dataset Aggregation (DAgger), combat challenges like distributional …
SAFE-GIL: SAFEty Guided Imitation Learning
Behavior Cloning is a popular approach to Imitation Learning, in which a robot observes an
expert supervisor and learns a control policy. However, behavior cloning suffers from the" …
expert supervisor and learns a control policy. However, behavior cloning suffers from the" …
Learning from demonstrations: An intuitive VR environment for imitation learning of construction robots
Construction robots are challenging the traditional paradigm of labor intensive and repetitive
construction tasks. Present concerns regarding construction robots are focused on their …
construction tasks. Present concerns regarding construction robots are focused on their …
Distributionally Robust Behavioral Cloning for Robust Imitation Learning
Robust reinforcement learning (RL) aims to learn a policy that can withstand uncertainties in
model parameters, which often arise in practical RL applications due to modeling errors in …
model parameters, which often arise in practical RL applications due to modeling errors in …
EKMP: Generalized imitation learning with adaptation, nonlinear hard constraints and obstacle avoidance
Y Huang - arXiv preprint arXiv:2103.00452, 2021 - arxiv.org
As a user-friendly and straightforward solution for robot trajectory generation, imitation
learning has been viewed as a vital direction in the context of robot skill learning. In contrast …
learning has been viewed as a vital direction in the context of robot skill learning. In contrast …
Asking for help: Failure prediction in behavioral cloning through value approximation
Recent progress in end-to-end Imitation Learning approaches has shown promising results
and generalization capabilities on mobile manipulation tasks. Such models are seeing …
and generalization capabilities on mobile manipulation tasks. Such models are seeing …