Aamir Ahmad

Aamir Ahmad
Universität Stuttgart · Institute of Flight Mechanics and Control

Doctor of Philosophy

About

43
Publications
6,093
Reads
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408
Citations
Citations since 2016
28 Research Items
352 Citations
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Introduction
I lead the Flight Robotics and Perception Group, which is co-located at the University of Stuttgart (Flight Robotics) and MPI Tübingen (Robot Perception). My research interests include State Estimation, Formation Control, Aerial Robotics, Multi-Robot Systems (aerial and ground robots), and Vision-based Aerial Perception.
Additional affiliations
May 2013 - August 2014
Technical University of Lisbon
Position
  • PostDoc Position

Publications

Publications (43)
Preprint
Full-text available
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 static camera, which acts as the reference frame for the mocap system. The calibration step has to be done a priori for every capture session, which is a tedious process, and...
Data
We bridged the sim-to-real gap by successfully flight-testing our novel end-to-end type autonomous soaring system. A deep artificial neural network featuring a Long Short-Term Memory implements the control policy for integrated updraft localization and exploitation. The recurrent structure facilitates observability and enables mapping the hard-to-...
Preprint
Full-text available
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. However, unlike multi-rotors, airships are severely motion constrained and affected by ambient wind. Their orientation and flight direction are also tightly coupled. Th...
Preprint
Full-text available
Coordinating groups of aircraft and unmanned aerial vehicles to reach target locations without collisions is crucial for deploying decentralized groups of vehicles in the real world. A key challenge is coordinating a variable number of agents without the need for agents to share information about their intended routes, reducing communication requir...
Article
Full-text available
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 (UAVs) with on-board RGB cameras and computation. Existing methods are limited by calibrated cameras and off-line processing. Thus, we present the first method (AirPose)...
Article
Full-text available
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 itself and map an unknown environment while maximizing the amount of information gained and consuming as low energy as possible. Leveraging the robot’s independent translati...
Preprint
Full-text available
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 work we developed a hardware and software-in-the-loop framework and a PID-based controller for large blimps in the presence of wind disturbance. However, blimps have a d...
Preprint
Full-text available
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 (UAVs) with on-board RGB cameras and computation. Existing methods are limited by calibrated cameras and off-line processing. Thus, we present the first method (AirPose)...
Chapter
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 airships, a simulation of which needs to address unique properties, i) dynamic deformation in response to aerodynamic and control forces, ii) high susceptibility to wind and turbulence a...
Preprint
Full-text available
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 tasks while being energy efficient, relatively silent and safe. To address the blimp navigation and control task, in our recent work, we have developed a software-in-the-loo...
Preprint
Full-text available
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 itself and map an unknown environment while maximizing the amount of information gained and consume as low energy as possible. Leveraging the robot’s independent translation...
Preprint
Full-text available
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 usually statically linked to the robot’s body, limiting the extra degrees of freedom for visual information acquisition. In this work, we overcome the aforementioned problem b...
Preprint
Full-text available
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 airships, a simulation of which needs to address unique properties, i) dynamic deformation in response to aerodynamic and control forces, ii) high susceptibility to wind and turbulence a...
Article
Full-text available
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 vision-based MoCap, where the objective is to estimate the trajectory of body pose and shape of a single moving person using multiple micro aerial vehicles. State-of-the-a...
Preprint
Full-text available
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 vision-based MoCap, where the objective is to estimate the trajectory of body pose and shape of a single moving person using multiple micro aerial vehicles. State-of-the-a...
Conference Paper
Full-text available
Capturing human motion in natural scenarios means moving motion capture out of the lab and into the wild. Typical approaches rely on fixed, calibrated, cameras and reflective markers on the body, significantly limiting the motions that can be captured. To make motion capture truly unconstrained, we describe the first fully autonomous outdoor captur...
Article
Full-text available
We present a novel robotic front-end for autonomous aerial motion-capture (mocap) in outdoor environments. In previous work, we presented an approach for cooperative detection and tracking (CDT) of a subject using multiple micro-aerial vehicles (MAVs). However, it did not ensure optimal view-point configurations of the MAVs to minimize the uncertai...
Preprint
Full-text available
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-free motion plans for a formation of mobile manipulator robots. Initially, collision-free configurations of a deformable 2-D virtual bounding box are identified, over a...
Preprint
Full-text available
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 while he/she performs physical activities, and ii) an algorithmic back-end that estimates full body human pose and shape from the saved videos. In this paper we present a...
Preprint
Full-text available
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 algorithm which is based on model predictive control (MPC). The planner is designed as a quadratic program, subject to constraints on robot dynamics and obstacle avoidance. Re...
Article
Full-text available
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 vehicles (MAVs) with on-board cameras only. The key enabling-aspect of our approach is the on-board person detection and tracking method. Recent state-of-the-art methods ba...
Article
In this paper, we present a unified approach for multi-robot cooperative simultaneous localization and object tracking based on particle filters. Our approach is scalable with respect to the number of robots in the team. We introduce a method that reduces, from an exponential to a linear growth, the space and computation time requirements with resp...
Chapter
Domestic assistance for the elderly and impaired people is one of the biggest upcoming challenges of our society. Consequently, in-home care through domestic service robots is identified as one of the most important application area of robotics research. Assistive tasks may range from visitor reception at the door to catering for owner’s small dail...
Article
In this article we present an online estimator for multirobot cooperative localization and target tracking based on nonlinear least squares minimization. Our method not only makes the rigorous optimization-based approach applicable online but also allows the estimator to be stable and convergent. We do so by employing a moving horizon technique to...
Article
Full-text available
The work presented in this paper is motivated by the goal of dependable autonomous navigation of mobile robots. This goal is a fundamental requirement for having autonomous robots in spaces such as domestic spaces and public establishments, left unattended by technical staff. In this paper we tackle this problem by taking an optimization approach:...
Article
In this paper we introduce a formation control loop that maximizes the performance of the cooperative perception of a tracked target by a team of mobile robots, while maintaining the team in formation, with a dynamically adjustable geometry which is a function of the quality of the target perception by the team. In the formation control loop, the c...
Article
This article presents a cooperative approach for tracking a moving spherical object in 3D space by a team of mobile robots equipped with sensors, in a highly dynamic environment. The tracker's core is a particle filter, modified to handle, within a single unified framework, the problem of complete or partial occlusion for some of the involved mobil...
Conference Paper
In this paper we address the problem of cooperative localization and target tracking with a team of moving robots. We model the problem as a least squares minimization problem and show that this problem can be efficiently solved using sparse optimization methods. To achieve this, we represent the problem as a graph, where the nodes are robot and ta...
Conference Paper
Full-text available
Maximizing the performance of cooperative perception of a tracked target by a team of mobile robots while maintaining the team's formation is the core problem addressed in this work. We propose a solution by integrating the controller and the estimator modules in a formation control loop. The controller module is a distributed non-linear model pred...
Conference Paper
Detection and tracking of an unknown-color spherical object in a partially-known environment using a robot with a single camera is the core problem addressed in this article. A novel color detection mechanism, which exploits the geometrical properties of the spherical object's projection onto the image plane, precedes the object's detection process...
Conference Paper
In this paper we describe a cooperative localization algorithm based on a modification of the Monte Carlo Localization algorithm where, when a robot detects it is lost, particles are spread not uniformly in the state space, but rather according to the information on the location of an object whose distance and bearing is measured by the lost robot....
Article
This paper presents design and development of a six legged robot with a total of 12 degrees of freedom, two in each limb and then an implementation of 'obstacle and undulated terrain-based' probabilistic roadmap method for motion planning of this hexaped which is able to negotiate large undulations as obstacles. The novelty in this implementation i...
Article
Full-text available
This work deals with a background subtraction algo- rithm for a fish-eye lens camera having 3 degrees of free- dom, 2 in translation and 1 in rotation. The core assump- tion in this algorithm is that the background is considered to be composed of a dominant static plane in the world frame. The novelty lies in developing a rank-constraint based back...
Article
Full-text available
This paper describes the status of the ISocRob MSL robotic soccer team as required by the RoboCup 2011 qualification procedures. The most rele-vant technical and scientifical developments carried out by the team, since its last participation in the RoboCup MSL competitions, are here detailed. These include cooperative localization, cooperative obje...

Questions

Question (1)
Question
cooperative perception may include cooperative localization, mapping, target tracking and so on.

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Projects

Projects (5)
Project
From the beginnings of aviation until today, new technologies - primarily in the fields of aerodynamics and lightweight construction - have been investigated, developed, and tested within the sport of gliding. Due to an increasing number of applications using unpiloted fixed-wing aircraft with long mission durations, the automation of tasks typical for soaring flight has become a focus of research in flight control. Besides that, its tactical nature and easy accessibility render autonomous soaring an ideal "playground" for research into modern control engineering methods, especially those from the field of artificial intelligence.
Project
Our goal is markless, unconstrained, human and animal motion capture outdoors. To that end, we are developing a flying mocap system using a team of aerial vehicles (MAVs) with only on-board, monocular RGB cameras. To realize such an outdoor motion capture system we need to address research challenges in both control and perception. In this project we address the perception problem. In a separate ongoing project we solve the control-related challenges, with perception problem in the loop. For more details, source code and data, please visit https://ps.is.tuebingen.mpg.de/research_projects/aircap
Project