Search Results for author: Vijay Kumar

Found 56 papers, 16 papers with code

Graph Neural Networks for Decentralized Multi-Agent Perimeter Defense

no code implementations23 Jan 2023 Elijah S. Lee, Lifeng Zhou, Alejandro Ribeiro, Vijay Kumar

In this work, we study the problem of decentralized multi-agent perimeter defense that asks for computing actions for defenders with local perceptions and communications to maximize the capture of intruders.

Imitation Learning

Reinforcement Learning for Agile Active Target Sensing with a UAV

no code implementations16 Dec 2022 Harsh Goel, Laura Jarin Lipschitz, Saurav Agarwal, Sandeep Manjanna, Vijay Kumar

Active target sensing is the task of discovering and classifying an unknown number of targets in an environment and is critical in search-and-rescue missions.

reinforcement-learning Reinforcement Learning (RL)

Vision-based Perimeter Defense via Multiview Pose Estimation

no code implementations25 Sep 2022 Elijah S. Lee, Giuseppe Loianno, Dinesh Jayaraman, Vijay Kumar

Previous studies in the perimeter defense game have largely focused on the fully observable setting where the true player states are known to all players.

Pose Estimation

Learning Decentralized Strategies for a Perimeter Defense Game with Graph Neural Networks

no code implementations24 Sep 2022 Elijah S. Lee, Lifeng Zhou, Alejandro Ribeiro, Vijay Kumar

We consider the problem of finding decentralized strategies for multi-agent perimeter defense games.

Learning Fashion Compatibility from In-the-wild Images

no code implementations13 Jun 2022 Additya Popli, Vijay Kumar, Sujit Jos, Saraansh Tandon

In this work, we propose to learn representations for compatibility prediction from in-the-wild street fashion images through self-supervised learning by leveraging the fact that people often wear compatible outfits.

Self-Supervised Learning

RTGNN: A Novel Approach to Model Stochastic Traffic Dynamics

no code implementations21 Feb 2022 Ke Sun, Stephen Chaves, Paul Martin, Vijay Kumar

Because it is difficult to develop first principle models of cars driven by humans, there is great potential for using data driven approaches in developing traffic dynamical models.

Decision Making Motion Planning +1

Dynamic Defender-Attacker Blotto Game

no code implementations18 Dec 2021 Daigo Shishika, Yue Guan, Michael Dorothy, Vijay Kumar

The game terminates with the attacker's win if any location has more attacker robots than defender robots at any time.

Learning Connectivity-Maximizing Network Configurations

no code implementations14 Dec 2021 Daniel Mox, Vijay Kumar, Alejandro Ribeiro

In this letter we propose a data-driven approach to optimizing the algebraic connectivity of a team of robots.


Beyond Robustness: A Taxonomy of Approaches towards Resilient Multi-Robot Systems

no code implementations25 Sep 2021 Amanda Prorok, Matthew Malencia, Luca Carlone, Gaurav S. Sukhatme, Brian M. Sadler, Vijay Kumar

In this survey article, we analyze how resilience is achieved in networks of agents and multi-robot systems that are able to overcome adversity by leveraging system-wide complementarity, diversity, and redundancy - often involving a reconfiguration of robotic capabilities to provide some key ability that was not present in the system a priori.

Large-scale Autonomous Flight with Real-time Semantic SLAM under Dense Forest Canopy

2 code implementations14 Sep 2021 Xu Liu, Guilherme V. Nardari, Fernando Cladera Ojeda, Yuezhan Tao, Alex Zhou, Thomas Donnelly, Chao Qu, Steven W. Chen, Roseli A. F. Romero, Camillo J. Taylor, Vijay Kumar

The autonomous navigation module utilizes a multi-level planning and mapping framework and computes dynamically feasible trajectories that lead the UAV to build a semantic map of the user-defined region of interest in a computationally and storage efficient manner.

Semantic Segmentation Semantic SLAM

Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selection

1 code implementation18 May 2021 Lifeng Zhou, Vishnu D. Sharma, QingBiao Li, Amanda Prorok, Alejandro Ribeiro, Pratap Tokekar, Vijay Kumar

We demonstrate the performance of our GNN-based learning approach in a scenario of active target tracking with large networks of robots.

Decision Making Motion Planning

Learning Connectivity for Data Distribution in Robot Teams

1 code implementation8 Mar 2021 Ekaterina Tolstaya, Landon Butler, Daniel Mox, James Paulos, Vijay Kumar, Alejandro Ribeiro

To overcome this challenge, we propose a task-agnostic, decentralized, low-latency method for data distribution in ad-hoc networks using Graph Neural Networks (GNN).

Large Scale Distributed Collaborative Unlabeled Motion Planning with Graph Policy Gradients

no code implementations11 Feb 2021 Arbaaz Khan, Vijay Kumar, Alejandro Ribeiro

We are able to demonstrate the scalability of our methods for a large number of robots by employing a graph neural network (GNN) to parameterize policies for the robots.

Motion Planning

Neurosymbolic Transformers for Multi-Agent Communication

1 code implementation NeurIPS 2020 Jeevana Priya Inala, Yichen Yang, James Paulos, Yewen Pu, Osbert Bastani, Vijay Kumar, Martin Rinard, Armando Solar-Lezama

We study the problem of inferring communication structures that can solve cooperative multi-agent planning problems while minimizing the amount of communication.

Place Recognition in Forests with Urquhart Tessellations

1 code implementation23 Sep 2020 Guilherme V. Nardari, Avraham Cohen, Steven W. Chen, Xu Liu, Vaibhav Arcot, Roseli A. F. Romero, Vijay Kumar

In this letter, we present a novel descriptor based on Urquhart tessellations derived from the position of trees in a forest.

Loop Closure Detection

Resilient Task Allocation in Heterogeneous Multi-Robot Systems

no code implementations9 Sep 2020 Siddharth Mayya, Diego S. D'antonio, David Saldaña, Vijay Kumar

For a multi-robot system equipped with heterogeneous capabilities, this paper presents a mechanism to allocate robots to tasks in a resilient manner when anomalous environmental conditions such as weather events or adversarial attacks affect the performance of robots within the tasks.

Multiagent Systems Robotics

Feedback Enhanced Motion Planning for Autonomous Vehicles

1 code implementation11 Jul 2020 Ke Sun, Brent Schlotfeldt, Stephen Chaves, Paul Martin, Gulshan Mandhyan, Vijay Kumar

In this work, we address the motion planning problem for autonomous vehicles through a new lattice planning approach, called Feedback Enhanced Lattice Planner (FELP).


TLIO: Tight Learned Inertial Odometry

no code implementations6 Jul 2020 Wenxin Liu, David Caruso, Eddy Ilg, Jing Dong, Anastasios I. Mourikis, Kostas Daniilidis, Vijay Kumar, Jakob Engel

We show that our network, trained with pedestrian data from a headset, can produce statistically consistent measurement and uncertainty to be used as the update step in the filter, and the tightly-coupled system outperforms velocity integration approaches in position estimates, and AHRS attitude filter in orientation estimates.

Graph Neural Networks for Motion Planning

no code implementations11 Jun 2020 Arbaaz Khan, Alejandro Ribeiro, Vijay Kumar, Anthony G. Francis

This paper investigates the feasibility of using Graph Neural Networks (GNNs) for classical motion planning problems.

Motion Planning

SLOAM: Semantic Lidar Odometry and Mapping for Forest Inventory

no code implementations29 Dec 2019 Steven W. Chen, Guilherme V. Nardari, Elijah S. Lee, Chao Qu, Xu Liu, Roseli A. F. Romero, Vijay Kumar

This paper describes an end-to-end pipeline for tree diameter estimation based on semantic segmentation and lidar odometry and mapping.

Semantic Segmentation

MAMPS: Safe Multi-Agent Reinforcement Learning via Model Predictive Shielding

no code implementations25 Oct 2019 Wenbo Zhang, Osbert Bastani, Vijay Kumar

Reinforcement learning is a promising approach to learning control policies for performing complex multi-agent robotics tasks.

Multi-agent Reinforcement Learning reinforcement-learning +1

Large Scale Model Predictive Control with Neural Networks and Primal Active Sets

no code implementations23 Oct 2019 Steven W. Chen, Tianyu Wang, Nikolay Atanasov, Vijay Kumar, Manfred Morari

The approach combines an offline-trained fully-connected neural network with an online primal active set solver.

PST900: RGB-Thermal Calibration, Dataset and Segmentation Network

1 code implementation20 Sep 2019 Shreyas S. Shivakumar, Neil Rodrigues, Alex Zhou, Ian D. Miller, Vijay Kumar, Camillo J. Taylor

In this work we propose long wave infrared (LWIR) imagery as a viable supporting modality for semantic segmentation using learning-based techniques.

Camera Calibration Semantic Segmentation +1

Mine Tunnel Exploration using Multiple Quadrupedal Robots

1 code implementation20 Sep 2019 Ian D. Miller, Fernando Cladera, Anthony Cowley, Shreyas S. Shivakumar, Elijah S. Lee, Laura Jarin-Lipschitz, Akhilesh Bhat, Neil Rodrigues, Alex Zhou, Avraham Cohen, Adarsh Kulkarni, James Laney, Camillo Jose Taylor, Vijay Kumar

Robotic exploration of underground environments is a particularly challenging problem due to communication, endurance, and traversability constraints which necessitate high degrees of autonomy and agility.


Perimeter-defense Game on Arbitrary Convex Shapes

no code implementations9 Sep 2019 Daigo Shishika, Vijay Kumar

Secondly, we solve the two vs. one game to introduce a cooperative pincer maneuver, where a pair of defenders team up to capture an intruder that cannot be captured by either one of the defender individually.

A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning

no code implementations CVPR 2019 Thanh-Toan Do, Toan Tran, Ian Reid, Vijay Kumar, Tuan Hoang, Gustavo Carneiro

Another approach explored in the field relies on an ad-hoc linearization (in terms of N) of the triplet loss that introduces class centroids, which must be optimized using the whole training set for each mini-batch - this means that a naive implementation of this approach has run-time complexity O(N^2).

Metric Learning Retrieval

Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks

1 code implementation25 Mar 2019 Ekaterina Tolstaya, Fernando Gama, James Paulos, George Pappas, Vijay Kumar, Alejandro Ribeiro

We consider the problem of finding distributed controllers for large networks of mobile robots with interacting dynamics and sparsely available communications.


DFineNet: Ego-Motion Estimation and Depth Refinement from Sparse, Noisy Depth Input with RGB Guidance

no code implementations15 Mar 2019 Yilun Zhang, Ty Nguyen, Ian D. Miller, Shreyas S. Shivakumar, Steven Chen, Camillo J. Taylor, Vijay Kumar

Depth estimation is an important capability for autonomous vehicles to understand and reconstruct 3D environments as well as avoid obstacles during the execution.

Autonomous Vehicles Depth Completion +2

DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth Completion

1 code implementation2 Feb 2019 Shreyas S. Shivakumar, Ty Nguyen, Ian D. Miller, Steven W. Chen, Vijay Kumar, Camillo J. Taylor

In this paper we propose a convolutional neural network that is designed to upsample a series of sparse range measurements based on the contextual cues gleaned from a high resolution intensity image.

Depth Completion Super-Resolution

Decentralization of Multiagent Policies by Learning What to Communicate

no code implementations24 Jan 2019 James Paulos, Steven W. Chen, Daigo Shishika, Vijay Kumar

Effective communication is required for teams of robots to solve sophisticated collaborative tasks.


Robustness Meets Deep Learning: An End-to-End Hybrid Pipeline for Unsupervised Learning of Egomotion

no code implementations20 Dec 2018 Alex Zihao Zhu, Wenxin Liu, ZiYun Wang, Vijay Kumar, Kostas Daniilidis

In this work, we propose a method that combines unsupervised deep learning predictions for optical flow and monocular disparity with a model based optimization procedure for instantaneous camera pose.

Optical Flow Estimation

Towards Search-based Motion Planning for Micro Aerial Vehicles

2 code implementations7 Oct 2018 Sikang Liu, Kartik Mohta, Nikolay Atanasov, Vijay Kumar

Search-based motion planning has been used for mobile robots in many applications.


Stochastic 2-D Motion Planning with a POMDP Framework

no code implementations29 Sep 2018 Ke Sun, Vijay Kumar

Motion planning is challenging when it comes to the case of imperfect state information.


Real Time Dense Depth Estimation by Fusing Stereo with Sparse Depth Measurements

1 code implementation20 Sep 2018 Shreyas S. Shivakumar, Kartik Mohta, Bernd Pfrommer, Vijay Kumar, Camillo J. Taylor

We present an approach to depth estimation that fuses information from a stereo pair with sparse range measurements derived from a LIDAR sensor or a range camera.

Depth Estimation

U-Net for MAV-based Penstock Inspection: an Investigation of Focal Loss in Multi-class Segmentation for Corrosion Identification

no code implementations18 Sep 2018 Ty Nguyen, Tolga Ozaslan, Ian D. Miller, James Keller, Giuseppe Loianno, Camillo J. Taylor, Daniel D. Lee, Vijay Kumar, Joseph H. Harwood, Jennifer Wozencraft

Periodical inspection and maintenance of critical infrastructure such as dams, penstocks, and locks are of significant importance to prevent catastrophic failures.

Spin-Boson Model to Demonstrate Quantum Tunneling in Biomolecules using IBM Quantum Computer

no code implementations1 Jul 2018 Yugojyoti Mohanta, Dhurjati Sai Abhishikth, Kuruva Pruthvi, Vijay Kumar, Bikash K. Behera, Prasanta K. Panigrahi

Efficient simulation of quantum mechanical problems can be performed in a quantum computer where the interactions of qubits lead to the realization of various problems possessing quantum nature.

Quantum Physics

Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients

no code implementations22 May 2018 Arbaaz Khan, Clark Zhang, Daniel D. Lee, Vijay Kumar, Alejandro Ribeiro

When the number of agents increases, the dimensionality of the input and control spaces increase as well, and these methods do not scale well.

Distributed Optimization Multi-agent Reinforcement Learning +2

Human Motion Capture Using a Drone

1 code implementation17 Apr 2018 Xiaowei Zhou, Sikang Liu, Georgios Pavlakos, Vijay Kumar, Kostas Daniilidis

Current motion capture (MoCap) systems generally require markers and multiple calibrated cameras, which can be used only in constrained environments.

Robust Fruit Counting: Combining Deep Learning, Tracking, and Structure from Motion

no code implementations1 Apr 2018 Xu Liu, Steven W. Chen, Shreyas Aditya, Nivedha Sivakumar, Sandeep Dcunha, Chao Qu, Camillo J. Taylor, Jnaneshwar Das, Vijay Kumar

We present a novel fruit counting pipeline that combines deep segmentation, frame to frame tracking, and 3D localization to accurately count visible fruits across a sequence of images.

The Multi Vehicle Stereo Event Camera Dataset: An Event Camera Dataset for 3D Perception

no code implementations30 Jan 2018 Alex Zihao Zhu, Dinesh Thakur, Tolga Ozaslan, Bernd Pfrommer, Vijay Kumar, Kostas Daniilidis

Event based cameras are a new passive sensing modality with a number of benefits over traditional cameras, including extremely low latency, asynchronous data acquisition, high dynamic range and very low power consumption.


Dense 3-D Mapping with Spatial Correlation via Gaussian Filtering

no code implementations23 Jan 2018 Ke Sun, Kelsey Saulnier, Nikolay Atanasov, George J. Pappas, Vijay Kumar

Many accurate and efficient methods exist that address this problem but most assume that the occupancy states of different elements in the map representation are statistically independent.


Fast, Autonomous Flight in GPS-Denied and Cluttered Environments

no code implementations6 Dec 2017 Kartik Mohta, Michael Watterson, Yash Mulgaonkar, Sikang Liu, Chao Qu, Anurag Makineni, Kelsey Saulnier, Ke Sun, Alex Zhu, Jeffrey Delmerico, Konstantinos Karydis, Nikolay Atanasov, Giuseppe Loianno, Davide Scaramuzza, Kostas Daniilidis, Camillo Jose Taylor, Vijay Kumar

One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a-priori knowledge of the operating environment.


Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight

11 code implementations30 Nov 2017 Ke Sun, Kartik Mohta, Bernd Pfrommer, Michael Watterson, Sikang Liu, Yash Mulgaonkar, Camillo J. Taylor, Vijay Kumar

However, we still encounter challenges in terms of improving the computational efficiency and robustness of the underlying algorithms for applications in autonomous flight with micro aerial vehicles in which it is difficult to use high quality sensors and pow- erful processors because of constraints on size and weight.


Memory Augmented Control Networks

no code implementations ICLR 2018 Arbaaz Khan, Clark Zhang, Nikolay Atanasov, Konstantinos Karydis, Vijay Kumar, Daniel D. Lee

The third part uses a network controller that learns to store those specific instances of past information that are necessary for planning.

Unsupervised Deep Homography: A Fast and Robust Homography Estimation Model

3 code implementations12 Sep 2017 Ty Nguyen, Steven W. Chen, Shreyas S. Shivakumar, Camillo J. Taylor, Vijay Kumar

Homography estimation between multiple aerial images can provide relative pose estimation for collaborative autonomous exploration and monitoring.

Homography Estimation Pose Estimation

Pose-Aware Person Recognition

no code implementations CVPR 2017 Vijay Kumar, Anoop Namboodiri, Manohar Paluri, C. V. Jawahar

Person recognition methods that use multiple body regions have shown significant improvements over traditional face-based recognition.

Person Recognition

Neural Network Memory Architectures for Autonomous Robot Navigation

no code implementations23 May 2017 Steven W. Chen, Nikolay Atanasov, Arbaaz Khan, Konstantinos Karydis, Daniel D. Lee, Vijay Kumar

This work is a first thorough study of memory structures for deep-neural-network-based robot navigation, and offers novel tools to train such networks from supervision and quantify their ability to generalize to unseen scenarios.

Robot Navigation

DimensionApp : android app to estimate object dimensions

no code implementations24 Sep 2016 Suriya Singh, Vijay Kumar

In this project, we develop an android app that uses on computer vision techniques to estimate an object dimension present in field of view.

Line Detection

Visual Phrases for Exemplar Face Detection

no code implementations ICCV 2015 Vijay Kumar, Anoop Namboodiri, C. V. Jawahar

Contrary to traditional approaches that model face variations from a large and diverse set of training examples, exemplar-based approaches use a collection of discriminatively trained exemplars for detection.

Face Detection Retrieval

Clustering by transitive propagation

no code implementations9 Jun 2015 Vijay Kumar, Dan Levy

We present a global optimization algorithm for clustering data given the ratio of likelihoods that each pair of data points is in the same cluster or in different clusters.

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