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Found 33 papers, 14 papers with code
Reslicing Ultrasound Images for Data Augmentation and Vessel Reconstruction
Robot-guided catheter insertion has the potential to deliver urgent medical care in situations where medical personnel are unavailable.
Enhanced Multi-Objective A* with Partial Expansion
The Multi-Objective Shortest Path Problem, typically posed on a graph, determines a set of paths from a start vertex to a destination vertex while optimizing multiple objectives.
Learning Modular Robot Locomotion from Demonstrations
This work presents a method that uses demonstrations from one set of designs to accelerate policy learning for additional designs.
Mathematical Justification of Hard Negative Mining via Isometric Approximation Theorem
In this paper, we utilize the mathematical theory of isometric approximation to show an equivalence between the Triplet Loss sampled by hard negative mining and an optimization problem that minimizes a Hausdorff-like distance between the neural network and its ideal counterpart function.
GLSO: Grammar-guided Latent Space Optimization for Sample-efficient Robot Design Automation
In this work, we present Grammar-guided Latent Space Optimization (GLSO), a framework that transforms design automation into a low-dimensional continuous optimization problem by training a graph variational autoencoder (VAE) to learn a mapping between the graph-structured design space and a continuous latent space.
iSimLoc: Visual Global Localization for Previously Unseen Environments with Simulated Images
The visual camera is an attractive device in beyond visual line of sight (B-VLOS) drone operation, since they are low in size, weight, power, and cost, and can provide redundant modality to GPS failures.
General Place Recognition Survey: Towards the Real-world Autonomy Age
A summary of this work and our datasets and evaluation API is publicly available to the robotics community at: https://github. com/MetaSLAM/GPRS.
Loop Closure Detection
Simultaneous Localization and Mapping
RGB-X Classification for Electronics Sorting
Conventional recycling processes rely on shredding and sorting waste streams, but for WEEE, which is comprised of numerous dissimilar materials, we explore targeted disassembly of numerous objects for improved material recovery.
ALTO: A Large-Scale Dataset for UAV Visual Place Recognition and Localization
We present the ALTO dataset, a vision-focused dataset for the development and benchmarking of Visual Place Recognition and Localization methods for Unmanned Aerial Vehicles.
AutoMerge: A Framework for Map Assembling and Smoothing in City-scale Environments
We present AutoMerge, a LiDAR data processing framework for assembling a large number of map segments into a complete map.
Enhanced Multi-Objective A* Using Balanced Binary Search Trees
This work addresses a Multi-Objective Shortest Path Problem (MO-SPP) on a graph where the goal is to find a set of Pareto-optimal solutions from a start node to a destination in the graph.
Learning Cooperative Multi-Agent Policies with Partial Reward Decoupling
One of the preeminent obstacles to scaling multi-agent reinforcement learning to large numbers of agents is assigning credit to individual agents' actions.
Subdimensional Expansion Using Attention-Based Learning For Multi-Agent Path Finding
By leveraging a Visual Transformer, we develop a learning-based single-agent planner, which plans for a single agent while paying attention to both the structure of the map and other agents with whom conflicts may happen.
Multi-Objective Path-Based D* Lite
Incremental graph search algorithms such as D* Lite reuse previous, and perhaps partial, searches to expedite subsequent path planning tasks.
Multi-objective Conflict-based Search Using Safe-interval Path Planning
This paper addresses a generalization of the well known multi-agent path finding (MAPF) problem that optimizes multiple conflicting objectives simultaneously such as travel time and path risk.
3D Segmentation Learning from Sparse Annotations and Hierarchical Descriptors
One of the main obstacles to 3D semantic segmentation is the significant amount of endeavor required to generate expensive point-wise annotations for fully supervised training.
i3dLoc: Image-to-range Cross-domain Localization Robust to Inconsistent Environmental Conditions
Based on such features, we further design a spherical convolution network to learn viewpoint-invariant symmetric place descriptors.
Learning Modular Robot Control Policies
One could craft a policy from scratch for each new design, but such an approach is not scalable, especially given the large number of designs that can be generated from even a small set of modules.
MS*: A New Exact Algorithm for Multi-agent Simultaneous Multi-goal Sequencing and Path Finding
In multi-agent applications such as surveillance and logistics, fleets of mobile agents are often expected to coordinate and safely visit a large number of goal locations as efficiently as possible.
Loosely Synchronized Search for Multi-agent Path Finding with Asynchronous Actions
Multi-agent path finding (MAPF) determines an ensemble of collision-free paths for multiple agents between their respective start and goal locations.
Subdimensional Expansion for Multi-objective Multi-agent Path Finding
One example of subdimensional expansion, when applied to A*, is called M* and M* was limited to a single objective function.
Interleaving Graph Search and Trajectory Optimization for Aggressive Quadrotor Flight
We introduce a framework for aggressive quadrotor trajectory generation with global reasoning capabilities that combines the best of trajectory optimization and discrete graph search.
Robotics
A Conflict-Based Search Framework for Multi-Objective Multi-Agent Path Finding
Naively applying existing multi-objective search algorithms, such as multi-objective A* (MOA*), to multi-agent path finding may prove to be inefficient as the dimensionality of the search space grows exponentially with the number of agents.
A Study of Domain Generalization on Ultrasound-based Multi-Class Segmentation of Arteries, Veins, Ligaments, and Nerves Using Transfer Learning
Identifying landmarks in the femoral area is crucial for ultrasound (US) -based robot-guided catheter insertion, and their presentation varies when imaged with different scanners.
Correspondence Matrices are Underrated
The loss functions that are optimized in these networks are based on the error in the transformation parameters.
MaskNet: A Fully-Convolutional Network to Estimate Inlier Points
We demonstrate these improvements on synthetic and real-world datasets.
One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment
We perform extensive simulation and real-world experiments to validate the efficacy of our approach and compare the performance with state-of-art approaches.
Adversary A3C for Robust Reinforcement Learning
Asynchronous Advantage Actor Critic (A3C) is an effective Reinforcement Learning (RL) algorithm for a wide range of tasks, such as Atari games and robot control.
FusionMapping: Learning Depth Prediction with Monocular Images and 2D Laser Scans
In this paper, we introduce a fusion-based depth prediction method, called FusionMapping.
xBD: A Dataset for Assessing Building Damage from Satellite Imagery
xBD is the largest building damage assessment dataset to date, containing 850, 736 building annotations across 45, 362 km\textsuperscript{2} of imagery.
Ranked #4 on
2D Semantic Segmentation
on xBD
Globally optimal registration of noisy point clouds
Registration of 3D point clouds is a fundamental task in several applications of robotics and computer vision.
PCRNet: Point Cloud Registration Network using PointNet Encoding
PointNet has recently emerged as a popular representation for unstructured point cloud data, allowing application of deep learning to tasks such as object detection, segmentation and shape completion.
Rapid Randomized Restarts for Multi-Agent Path Finding Solvers
Multi-Agent Path Finding (MAPF) is an NP-hard problem well studied in artificial intelligence and robotics.
