Mobile robotics applications

Mobile robotics related applications are one of the most emerging ones on the market, including aerial, ground and underwater variants. This trend is likely to be continued in the near future too, as long as companies such as Google, Bosch, Toyota are heavily interested and investigating into the future autonomous car.

The main components of a mobile robot include the perception, localization&mapping, planning and low lever control parts. Perception is essential in order to receive and interpret the information from the environment. We use different sensors for this, like IMU, stereo camera, 3D laser or the popular kinect camera. Localization&mapping is referring to the ability of the robot to answer the question where am I with respect to some map information. The creation of a map is strongly related to the localization, as these two are related to each other, usually denoted as simultaneous localization and mapping (SLAM) within the robotics. The planning of the robot gives an answer to the question where I go, and how do I get there. This incorporates advanced reasoning and AI methods too. Finally, the low level control translates the higher level planning command to the robot actuators taking into account the kinematic and dynamical model of the device.

We focus on the application side of these techniques using different platforms that we have in our laboratory, mainly developing code within the ROS framework in C++. Special research topics from these applications are treated in the other research directions from our group.

Our open and ongoing projects in this area are listed below, together with a selection of completed projects where relevant.

1 postdoc, 2 PhDs: Robotic mapping of sea litter using learning and active sensing

We are hiring 1 postdoctoral researcher and 2 PhD students on mapping of sea litter using a mixed team of aerial (quadcopter), surface, and underwater robots; in the framework of the European project SeaClear, http://seaclear-project.eu. We will exploit machine learning and active sensing techniques to map litter both on the sea bottom and at the surface.

H2020 SeaClear - Search, Identification, and Collection of Marine Litter with Autonomous Robots

Litter disposal and accumulation in the marine environment is one of the fastest growing threats to the world's oceans. Plastic is the most common type of litter found on the seafloor, but the list is long and includes glass, metal, wood and clothing. The EU-funded SeaClear project is developing autonomous robots for underwater littler collection using new debris mapping, classification, and collection systems. Specifically, the project will build a mixed team of unmanned underwater, surface and aerial vehicles to find and collect litter from the seabed.

AIRGUIDE: A Learning Aerial Guide for the Elderly and Disabled

Robotic assistants can greatly improve the life of the ever-increasing elderly and disabled population. However, current efforts in assistive robotics are focused on ground robots and manipulators in controlled, indoor environments. AIRGUIDE will break away from this by exploiting unmanned aerial vehicles (UAVs) and their versatile motion capabilities. Specifically, the project will develop aerial assistive technology for independent mobility of an elderly or disabled person over a wide, outdoor area, via monitoring risks and guiding the person when needed.

3D object recognition with mobile robots - PN3-Innovative-Cheques

The main aim of the project is the application of the techniques developed by the academic partner in the industrial environment from the beneficiary. The developed open-source modules are reusable and they can be adopted to the needs of the industrial beneficial. In order to close the perception-planning loop active perception techniques are proposed to be used also for the mapping application part. 

Active Perception for Flexible Object Handling in Smart Manufacturing

Intelligent object handling is becoming a must in a smart manufacturing system especially with the recent appearance of the motion compliant dual handed industrial robotic systems. Also the enhanced 3D sensing capabilities from the robotics domain enables us to reconsider our view about the smart manufacturing by enabling on the fly spatial perception of the robot working space.

Learning radio or litter maps with mobile robots

Mobile robots often need to learn an initially uknown map of a position-dependent parameter from sampled values. Examples include learning a map of radio transmission rates, or a map with the density of litter at each point. Moreover, learning this map is often only one part of the robot's task -- the robot may also have a navigation objective, low energy consumption goals, etc. In this project, we aim to design and study a robot motion control strategy that optimally takes into account both map learning and the other objectives of the robot.

Assistive robot arms

Robots that assist elderly or disabled persons in their day-to-day tasks can lead to a huge improvement in quality of life. At ROCON we are pursuing assistive manipulators, as well as UAVs for monitoring at-risk persons. This project focuses on the first direction, and presents a wide range of opportunities for a team of students, starting from low-level control design and vision tasks, to high-level control using artificial intelligence tools. Each student will work on one well-defined subtopic in these areas. Specific tasks include:

Assistive autonomous UAVs

Robots that assist elderly or disabled persons in their day-to-day tasks can lead to a huge improvement in quality of life. This project employs UAVs to monitor at-risk persons, and research challenges range from real-time observation and observation to high-level vision and control for person monitoring. The project is appropriate for a team of students, each of them working on a well-defined subtask, such as:

AI based corridor racing

Ready for playing with an autonomous racing car? Join this project to learn AI related topics in the era of autonomous driving.

You should be interested/motivated in the fields:

  • Computer science
  • Image processing
  • Robotics

Mapping with mobile robots

The main aim of the project is to develop a robot being able to add semantic 3D information to an indoor map. The developed would be based on existing open-source modules in cooperation with Analog Devices.

Currently the company is producing a brand new 3 TOF depth camera. Within this project, the robot would be augmented with additional 3D sensors in order to facilitate the semantic mapping. 

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