Search Results for author: Maani Ghaffari

Found 25 papers, 22 papers with code

ConvBKI: Real-Time Probabilistic Semantic Mapping Network with Quantifiable Uncertainty

no code implementations24 Oct 2023 Joey Wilson, Yuewei Fu, Joshua Friesen, Parker Ewen, Andrew Capodieci, Paramsothy Jayakumar, Kira Barton, Maani Ghaffari

In this paper, we develop a modular neural network for real-time semantic mapping in uncertain environments, which explicitly updates per-voxel probabilistic distributions within a neural network layer.

Semantic Segmentation

Lie Neurons: Adjoint-Equivariant Neural Networks for Semisimple Lie Algebras

1 code implementation6 Oct 2023 Tzu-Yuan Lin, Minghan Zhu, Maani Ghaffari

This paper proposes an equivariant neural network that takes data in any semi-simple Lie algebra as input.

Point Cloud Registration

Convolutional Bayesian Kernel Inference for 3D Semantic Mapping

2 code implementations21 Sep 2022 Joey Wilson, Yuewei Fu, Arthur Zhang, Jingyu Song, Andrew Capodieci, Paramsothy Jayakumar, Kira Barton, Maani Ghaffari

Robotic perception is currently at a cross-roads between modern methods, which operate in an efficient latent space, and classical methods, which are mathematically founded and provide interpretable, trustworthy results.

Bayesian Inference

SoLo T-DIRL: Socially-Aware Dynamic Local Planner based on Trajectory-Ranked Deep Inverse Reinforcement Learning

1 code implementation16 Sep 2022 Yifan Xu, Theodor Chakhachiro, Tribhi Kathuria, Maani Ghaffari

This work proposes a new framework for a socially-aware dynamic local planner in crowded environments by building on the recently proposed Trajectory-ranked Maximum Entropy Deep Inverse Reinforcement Learning (T-MEDIRL).

Navigate Social Navigation

E2PN: Efficient SE(3)-Equivariant Point Network

1 code implementation CVPR 2023 Minghan Zhu, Maani Ghaffari, William A. Clark, Huei Peng

We also propose a permutation layer to recover SO(3) features from spherical features to preserve the capacity to distinguish rotations.

Pose Estimation

MotionSC: Data Set and Network for Real-Time Semantic Mapping in Dynamic Environments

1 code implementation14 Mar 2022 Joey Wilson, Jingyu Song, Yuewei Fu, Arthur Zhang, Andrew Capodieci, Paramsothy Jayakumar, Kira Barton, Maani Ghaffari

This work addresses a gap in semantic scene completion (SSC) data by creating a novel outdoor data set with accurate and complete dynamic scenes.

Fusing Convolutional Neural Network and Geometric Constraint for Image-based Indoor Localization

no code implementations5 Jan 2022 Jingwei Song, Mitesh Patel, Maani Ghaffari

This paper proposes a new image-based localization framework that explicitly localizes the camera/robot by fusing Convolutional Neural Network (CNN) and sequential images' geometric constraints.

Image-Based Localization Indoor Localization +1

Dynamic Semantic Occupancy Mapping using 3D Scene Flow and Closed-Form Bayesian Inference

2 code implementations6 Aug 2021 Aishwarya Unnikrishnan, Joey Wilson, Lu Gan, Andrew Capodieci, Paramsothy Jayakumar, Kira Barton, Maani Ghaffari

This paper reports on a dynamic semantic mapping framework that incorporates 3D scene flow measurements into a closed-form Bayesian inference model.

Bayesian Inference Semantic Segmentation

Correspondence-Free Point Cloud Registration with SO(3)-Equivariant Implicit Shape Representations

1 code implementation21 Jul 2021 Minghan Zhu, Maani Ghaffari, Huei Peng

We learn an embedding for each point cloud in a feature space that preserves the SO(3)-equivariance property, enabled by recent developments in equivariant neural networks.

Point Cloud Registration

Bayesian dense inverse searching algorithm for real-time stereo matching in minimally invasive surgery

1 code implementation14 Jun 2021 Jingwei Song, Qiuchen Zhu, Jianyu Lin, Maani Ghaffari

Our Bayesian method correctly balances the probability of the patch for stereo images at different scales.

Stereo Matching

Global Unifying Intrinsic Calibration for Spinning and Solid-State LiDARs

5 code implementations6 Dec 2020 Jiunn-Kai Huang, Chenxi Feng, Madhav Achar, Maani Ghaffari, Jessy W. Grizzle

By modeling the calibration parameters as an element of a special matrix Lie Group, we achieve a unifying view of calibration for different types of LiDARs.

A New Framework for Registration of Semantic Point Clouds from Stereo and RGB-D Cameras

1 code implementation10 Nov 2020 Ray Zhang, Tzu-Yuan Lin, Chien Erh Lin, Steven A. Parkison, William Clark, Jessy W. Grizzle, Ryan M. Eustice, Maani Ghaffari

This paper reports on a novel nonparametric rigid point cloud registration framework that jointly integrates geometric and semantic measurements such as color or semantic labels into the alignment process and does not require explicit data association.

Point Cloud Registration

A Closed-Form Uncertainty Propagation in Non-Rigid Structure from Motion

1 code implementation10 May 2020 Jingwei Song, Mitesh Patel, Ashkan Jasour, Maani Ghaffari

In this paper, we present a statistical inference on the element-wise uncertainty quantification of the estimated deforming 3D shape points in the case of the exact low-rank SDP problem.

Uncertainty Quantification

Monocular Depth Prediction through Continuous 3D Loss

2 code implementations21 Mar 2020 Minghan Zhu, Maani Ghaffari, Yuanxin Zhong, Pingping Lu, Zhong Cao, Ryan M. Eustice, Huei Peng

In contrast to the current point-to-point loss evaluation approach, the proposed 3D loss treats point clouds as continuous objects; therefore, it compensates for the lack of dense ground truth depth due to LIDAR's sparsity measurements.

Depth Estimation Depth Prediction

DeepLocNet: Deep Observation Classification and Ranging Bias Regression for Radio Positioning Systems

1 code implementation2 Feb 2020 Sahib Singh Dhanjal, Maani Ghaffari, Ryan M. Eustice

The proposed algorithm can globally localize and track a smartphone (or robot) with a priori unknown location, and with a semi-accurate prior map (error within 0. 8 m) of the WiFi Access Points (AP).

Robotics Signal Processing

Nonparametric Continuous Sensor Registration

2 code implementations8 Jan 2020 William Clark, Maani Ghaffari, Anthony Bloch

The functions can be defined on arbitrary smooth manifolds where the action of a Lie group aligns them.

Point Cloud Registration Visual Odometry

A Keyframe-based Continuous Visual SLAM for RGB-D Cameras via Nonparametric Joint Geometric and Appearance Representation

1 code implementation2 Dec 2019 Xi Lin, Dingyi Sun, Tzu-Yuan Lin, Ryan M. Eustice, Maani Ghaffari

The experimental evaluations using publicly available RGB-D benchmarks show that the developed keyframe selection technique using continuous visual odometry outperforms its robust dense (and direct) visual odometry equivalent.

Visual Odometry

Adaptive Continuous Visual Odometry from RGB-D Images

1 code implementation1 Oct 2019 Tzu-Yuan Lin, William Clark, Ryan M. Eustice, Jessy W. Grizzle, Anthony Bloch, Maani Ghaffari

In this paper, we extend the recently developed continuous visual odometry framework for RGB-D cameras to an adaptive framework via online hyperparameter learning.

Visual Odometry

Bayesian Spatial Kernel Smoothing for ScalableDense Semantic Mapping

2 code implementations10 Sep 2019 Lu Gan, Ray Zhang, Jessy W. Grizzle, Ryan M. Eustice, Maani Ghaffari

This paper develops a Bayesian continuous 3D semantic occupancy map from noisy point cloud measurements.


LiDARTag: A Real-Time Fiducial Tag System for Point Clouds

4 code implementations23 Aug 2019 Jiunn-Kai Huang, Shoutian Wang, Maani Ghaffari, Jessy W. Grizzle

Because of the LiDAR sensors' nature, rapidly changing ambient lighting will not affect the detection of a LiDARTag; hence, the proposed fiducial marker can operate in a completely dark environment.

Object Tracking Sensor Fusion +2

Contact-Aided Invariant Extended Kalman Filtering for Robot State Estimation

1 code implementation19 Apr 2019 Ross Hartley, Maani Ghaffari, Ryan M. Eustice, Jessy W. Grizzle

This filter combines contact-inertial dynamics with forward kinematic corrections to estimate pose and velocity along with all current contact points.


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