A survey of contextual optimization methods for decision-making under uncertainty
Recently there has been a surge of interest in operations research (OR) and the machine
learning (ML) community in combining prediction algorithms and optimization techniques to …
learning (ML) community in combining prediction algorithms and optimization techniques to …
Digital twins in wind energy: Emerging technologies and industry-informed future directions
This article presents a comprehensive overview of the digital twin technology and its
capability levels, with a specific focus on its applications in the wind energy industry. It …
capability levels, with a specific focus on its applications in the wind energy industry. It …
Se (3)-diffusionfields: Learning smooth cost functions for joint grasp and motion optimization through diffusion
Multi-objective optimization problems are ubiquitous in robotics, eg, the optimization of a
robot manipulation task requires a joint consideration of grasp pose configurations …
robot manipulation task requires a joint consideration of grasp pose configurations …
Differentiable integrated motion prediction and planning with learnable cost function for autonomous driving
Predicting the future states of surrounding traffic participants and planning a safe, smooth,
and socially compliant trajectory accordingly are crucial for autonomous vehicles (AVs) …
and socially compliant trajectory accordingly are crucial for autonomous vehicles (AVs) …
NeuralFeels with neural fields: Visuotactile perception for in-hand manipulation
To achieve human-level dexterity, robots must infer spatial awareness from multimodal
sensing to reason over contact interactions. During in-hand manipulation of novel objects …
sensing to reason over contact interactions. During in-hand manipulation of novel objects …
Object pose estimation with statistical guarantees: Conformal keypoint detection and geometric uncertainty propagation
The two-stage object pose estimation paradigm first detects semantic keypoints on the
image and then estimates the 6D pose by minimizing reprojection errors. Despite performing …
image and then estimates the 6D pose by minimizing reprojection errors. Despite performing …
Autonomous drone racing: A survey
Over the last decade, the use of autonomous drone systems for surveying, search and
rescue, or last-mile delivery has increased exponentially. With the rise of these applications …
rescue, or last-mile delivery has increased exponentially. With the rise of these applications …
Actor-critic model predictive control
A Romero, Y Song… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
An open research question in robotics is how to combine the benefits of model-free
reinforcement learning (RL)—known for its strong task performance and flexibility in …
reinforcement learning (RL)—known for its strong task performance and flexibility in …
Tta-cope: Test-time adaptation for category-level object pose estimation
Test-time adaptation methods have been gaining attention recently as a practical solution for
addressing source-to-target domain gaps by gradually updating the model without requiring …
addressing source-to-target domain gaps by gradually updating the model without requiring …
Surco: Learning linear surrogates for combinatorial nonlinear optimization problems
Optimization problems with nonlinear cost functions and combinatorial constraints appear in
many real-world applications but remain challenging to solve efficiently compared to their …
many real-world applications but remain challenging to solve efficiently compared to their …