no code implementations • 23 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.
no code implementations • 16 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.
no code implementations • 3 Nov 2022 • Ioannis Mavromatis, Adrian Sanchez-Mompo, Francesco Raimondo, James Pope, Marcello Bullo, Ingram Weeks, Vijay Kumar, Pietro Carnelli, George Oikonomou, Theodoros Spyridopoulos, Aftab Khan
Our framework is also generalisable, adapting to new sensor streams and environments with minimal online reconfiguration.
no code implementations • 25 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.
no code implementations • 24 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.
no code implementations • 13 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.
no code implementations • 21 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.
no code implementations • 18 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.
no code implementations • 14 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.
no code implementations • 25 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.
no code implementations • 16 Sep 2021 • Ambareesh Revanur, Vijay Kumar, Deepthi Sharma
We consider the problem of complementary fashion prediction.
Ranked #2 on Recommendation Systems on Polyvore
2 code implementations • 14 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.
1 code implementation • 18 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.
1 code implementation • 8 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).
no code implementations • 11 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.
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.
1 code implementation • 23 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.
no code implementations • 22 Sep 2020 • Ty Nguyen, Ian D. Miller, Avi Cohen, Dinesh Thakur, Shashank Prasad, Camillo J. Taylor, Pratik Chaudrahi, Vijay Kumar
Scalable training data generation is a critical problem in deep learning.
no code implementations • 9 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
1 code implementation • 11 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).
no code implementations • 6 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.
no code implementations • 11 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.
no code implementations • 29 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.
no code implementations • 25 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
no code implementations • 23 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.
1 code implementation • 20 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.
Ranked #3 on Thermal Image Segmentation on PST900
1 code implementation • 20 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.
no code implementations • 9 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.
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).
1 code implementation • 3 Apr 2019 • Ty Nguyen, Shreyas S. Shivakumar, Ian D. Miller, James Keller, Elijah S. Lee, Alex Zhou, Tolga Ozaslan, Giuseppe Loianno, Joseph H. Harwood, Jennifer Wozencraft, Camillo J. Taylor, Vijay Kumar
Real-time semantic image segmentation on platforms subject to size, weight and power (SWaP) constraints is a key area of interest for air surveillance and inspection.
1 code implementation • 25 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.
no code implementations • 15 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.
1 code implementation • 2 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.
no code implementations • 24 Jan 2019 • James Paulos, Steven W. Chen, Daigo Shishika, Vijay Kumar
Effective communication is required for teams of robots to solve sophisticated collaborative tasks.
no code implementations • 20 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.
no code implementations • 4 Nov 2018 • Xu Liu, Steven W. Chen, Chenhao Liu, Shreyas S. Shivakumar, Jnaneshwar Das, Camillo J. Taylor, James Underwood, Vijay Kumar
We present a cheap, lightweight, and fast fruit counting pipeline that uses a single monocular camera.
2 code implementations • 7 Oct 2018 • Sikang Liu, Kartik Mohta, Nikolay Atanasov, Vijay Kumar
Search-based motion planning has been used for mobile robots in many applications.
no code implementations • 29 Sep 2018 • Ke Sun, Vijay Kumar
Motion planning is challenging when it comes to the case of imperfect state information.
no code implementations • 27 Sep 2018 • Arbaaz Khan, Clark Zhang, Vijay Kumar, Alejandro Ribeiro
A deep reinforcement learning solution is developed for a collaborative multiagent system.
1 code implementation • 20 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.
no code implementations • 18 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.
no code implementations • 1 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.
no code implementations • 22 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
1 code implementation • 17 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.
no code implementations • 1 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.
no code implementations • 30 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.
no code implementations • 23 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.
no code implementations • 6 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.
11 code implementations • 30 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.
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.
3 code implementations • 12 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.
Ranked #4 on Homography Estimation on S-COCO
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.
no code implementations • 23 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.
no code implementations • 24 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.
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.
no code implementations • 9 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.