65 citations · 302 across the 20 of their papers we have counts for
21 papers
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…
Learning from synthetic data generated with GRADE
Elia Bonetto, Chenghao Xu, Aamir Ahmad
Recently, synthetic data generation and realistic rendering has advanced tasks like target tracking and human pose estimation. Simulations for most robotics applications are obtain…
Synthetic Data-based Detection of Zebras in Drone Imagery
Elia Bonetto, Aamir Ahmad
Nowadays, there is a wide availability of datasets that enable the training of common object detectors or human detectors. These come in the form of labelled real-world images and…
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…
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…
Accelerated Video Annotation driven by Deep Detector and Tracker
Eric Price, Aamir Ahmad
Annotating object ground truth in videos is vital for several downstream tasks in robot perception and machine learning, such as for evaluating the performance of an object tracker…
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…
SmartMocap: Joint Estimation of Human and Camera Motion using Uncalibrated RGB Cameras
Nitin Saini, Chun-hao P. Huang, Michael J. Black +1
Markerless human motion capture (mocap) from multiple RGB cameras is a widely studied problem. Existing methods either need calibrated cameras or calibrate them relative to a stati…
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…
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…
AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation
Nitin Saini, Elia Bonetto, Eric Price +2
In this letter, we present a novel markerless 3D human motion capture (MoCap) system for unstructured, outdoor environments that uses a team of autonomous unmanned aerial vehicles…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…