activity
20182023
most citedDeep Neural Network-based Cooperative Visual Tracking through Multiple Micro Aerial Vehicles

65 citations · 302 across the 20 of their papers we have counts for

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16 papers · 1 filter

cs.RO2023

Simulation of Dynamic Environments for SLAM

Elia Bonetto, Chenghao Xu, Aamir Ahmad

Simulation engines are widely adopted in robotics. However, they lack either full simulation control, ROS integration, realistic physics, or photorealism. Recently, synthetic data…

cs.RO2023

Multi-Task Reinforcement Learning in Continuous Control with Successor Feature-Based Concurrent Composition

Yu Tang Liu, Aamir Ahmad

Deep reinforcement learning (DRL) frameworks are increasingly used to solve high-dimensional continuous control tasks in robotics. However, due to the lack of sample efficiency, ap…

cs.RO2023★ 2 cited

GRADE: Generating Realistic And Dynamic Environments for Robotics Research with Isaac Sim

Elia Bonetto, Chenghao Xu, Aamir Ahmad

Synthetic data and novel rendering techniques have greatly influenced computer vision research in tasks like target tracking and human pose estimation. However, robotics research h…

cs.RO2023★ 1 cited

Reinforcement Learning based Autonomous Multi-Rotor Landing on Moving Platforms

Pascal Goldschmid, Aamir Ahmad

Multi-rotor UAVs suffer from a restricted range and flight duration due to limited battery capacity. Autonomous landing on a 2D moving platform offers the possibility to replenish…

cs.RO2022★ 15 cited

Viewpoint-driven Formation Control of Airships for Cooperative Target Tracking

Eric Price, Michael J. Black, Aamir Ahmad

For tracking and motion capture (MoCap) of animals in their natural habitat, a formation of safe and silent aerial platforms, such as airships with on-board cameras, is well suited…

cs.RO2022★ 1 cited

Deep Residual Reinforcement Learning based Autonomous Blimp Control

Yu Tang Liu, Eric Price, Michael J. Black +1

Blimps are well suited to perform long-duration aerial tasks as they are energy efficient, relatively silent and safe. To address the blimp navigation and control task, in previous…

cs.RO2021★ 8 cited

Autonomous Blimp Control using Deep Reinforcement Learning

Yu Tang Liu, Eric Price, Pascal Goldschmid +2

Aerial robot solutions are becoming ubiquitous for an increasing number of tasks. Among the various types of aerial robots, blimps are very well suited to perform long-duration tas…

cs.RO2021

Collaborative Mapping of Archaeological Sites using multiple UAVs

Manthan Patel, Aditya Bandopadhyay, Aamir Ahmad

UAVs have found an important application in archaeological mapping. Majority of the existing methods employ an offline method to process the data collected from an archaeological s…

cs.RO2021★ 7 cited

Active Visual SLAM with Independently Rotating Camera

Elia Bonetto, Pascal Goldschmid, Michael J. Black +1

In active Visual-SLAM (V-SLAM), a robot relies on the information retrieved by its cameras to control its own movements for autonomous mapping of the environment. Cameras are usual…

cs.RO2021★ 39 cited

iRotate: Active Visual SLAM for Omnidirectional Robots

Elia Bonetto, Pascal Goldschmid, Michael Pabst +2

In this paper, we present an active visual SLAM approach for omnidirectional robots. The goal is to generate control commands that allow such a robot to simultaneously localize its…

cs.RO2020★ 13 cited

Simulation and Control of Deformable Autonomous Airships in Turbulent Wind

Eric Price, Yu Tang Liu, Michael J. Black +1

Abstract. Fixed wing and multirotor UAVs are common in the field of robotics. Solutions for simulation and control of these vehicles are ubiquitous. This is not the case for airshi…

cs.RO2020★ 1 cited

AirCapRL: Autonomous Aerial Human Motion Capture using Deep Reinforcement Learning

Rahul Tallamraju, Nitin Saini, Elia Bonetto +4

In this letter, we introduce a deep reinforcement learning (RL) based multi-robot formation controller for the task of autonomous aerial human motion capture (MoCap). We focus on v…

cs.RO2019

Motion Planning for Multi-Mobile-Manipulator Payload Transport Systems

Rahul Tallamraju, Durgesh Haribhau Salunkhe, Sujit Rajappa +3

In this paper, a kinematic motion planning algorithm for cooperative spatial payload manipulation is presented. A hierarchical approach is introduced to compute real-time collision…

cs.RO2019★ 58 cited

Active Perception based Formation Control for Multiple Aerial Vehicles

Rahul Tallamraju, Eric Price, Roman Ludwig +4

Autonomous motion capture (mocap) systems for outdoor scenarios involving flying or mobile cameras rely on i) a robotic front-end to track and follow a human subject in real-time w…

cs.RO2018★ 44 cited

Decentralized MPC based Obstacle Avoidance for Multi-Robot Target Tracking Scenarios

Rahul Tallamraju, Sujit Rajappa, Michael Black +2

In this work, we consider the problem of decentralized multi-robot target tracking and obstacle avoidance in dynamic environments. Each robot executes a local motion planning algor…

cs.RO2018★ 65 cited

Deep Neural Network-based Cooperative Visual Tracking through Multiple Micro Aerial Vehicles

Eric Price, Guilherme Lawless, Heinrich H. Bülthoff +2

Multi-camera full-body pose capture of humans and animals in outdoor environments is a highly challenging problem. Our approach to it involves a team of cooperating micro aerial ve…