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Found 16 papers, 4 papers with code
DPPE: Dense Pose Estimation in a Plenoxels Environment using Gradient Approximation
In particular, we examine an approach that takes advantage of the rapid rendering speed of Plenoxels to numerically approximate part of the pose gradient, using a central differencing technique.
DIO: Dataset of 3D Mesh Models of Indoor Objects for Robotics and Computer Vision Applications
These images were processed using a photogrammetry software known as Meshroom to generate a dense surface reconstruction of the scene.
Parallel Reinforcement Learning Simulation for Visual Quadrotor Navigation
Gathering data for RL is known to be a laborious task, and real-world experiments can be risky.
Systematic Comparison of Path Planning Algorithms using PathBench
An unified path planning interface that facilitates the development and benchmarking of existing and new algorithms is needed.
Pareto Frontier Approximation Network (PA-Net) to Solve Bi-objective TSP
The travelling salesperson problem (TSP) is a classic resource allocation problem used to find an optimal order of doing a set of tasks while minimizing (or maximizing) an associated objective function.
RL-PGO: Reinforcement Learning-based Planar Pose-Graph Optimization
The objective of pose SLAM or pose-graph optimization (PGO) is to estimate the trajectory of a robot given odometric and loop closing constraints.
A Robot Web for Distributed Many-Device Localisation
We show that a distributed network of robots or other devices which make measurements of each other can collaborate to globally localise via efficient ad-hoc peer to peer communication.
Pareto Frontier Approximation Network (PA-Net) Applied to Multi-objective TSP
In this work, we present PA-Net, a network that generates good approximations of the Pareto front for the multi-objective optimization problems.
PathBench: A Benchmarking Platform for Classical and Learned Path Planning Algorithms
Path planning is a key component in mobile robotics.
Waypoint Planning Networks
We propose waypoint planning networks (WPN), a hybrid algorithm based on LSTMs with a local kernel - a classic algorithm such as A*, and a global kernel using a learned algorithm.
Cain: Automatic Code Generation for Simultaneous Convolutional Kernels on Focal-plane Sensor-processors
Focal-plane Sensor-processors (FPSPs) are a camera technology that enable low power, high frame rate computation, making them suitable for edge computation.
AnalogNet: Convolutional Neural Network Inference on Analog Focal Plane Sensor Processors
We present a high-speed, energy-efficient Convolutional Neural Network (CNN) architecture utilising the capabilities of a unique class of devices known as analog Focal Plane Sensor Processors (FPSP), in which the sensor and the processor are embedded together on the same silicon chip.
BIT-VO: Visual Odometry at 300 FPS using Binary Features from the Focal Plane
Focal-plane Sensor-processor (FPSP) is a next-generation camera technology which enables every pixel on the sensor chip to perform computation in parallel, on the focal plane where the light intensity is captured.
InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Dataset
Datasets have gained an enormous amount of popularity in the computer vision community, from training and evaluation of Deep Learning-based methods to benchmarking Simultaneous Localization and Mapping (SLAM).
Navigating the Landscape for Real-time Localisation and Mapping for Robotics and Virtual and Augmented Reality
Visual understanding of 3D environments in real-time, at low power, is a huge computational challenge.
Algorithmic Performance-Accuracy Trade-off in 3D Vision Applications Using HyperMapper
In this paper we investigate an emerging application, 3D scene understanding, likely to be significant in the mobile space in the near future.
