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.

Horizon Europe SeaClear2.0: Scalable Full-Cycle Marine Litter Remediation in the Mediterranean: Robotic and Participatory Solutions

Today’s oceans contain roughly 25 million tons of plastic waste. Over 90% of all marine litter is located on the seafloor, making it difficult and expensive to collect. Every year, up to 600,000 tones of macroplastics and microplastics enter European seas. While plastic pollution affects all seas across Europe, the Mediterranean is the most affected sea, due to its semi-enclosed basin and the intense human activities taking place on the surrounding coastal areas. 

Fast map learning with mobile robots

Mobile robots often need to learn an initially uknown map of a position-dependent parameter from sampled values. Examples include learning radio transmission rates, the density of litter at each point, forest density, etc. 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.

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.

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.

Industrial 3D perception

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 and Robotics.AI.

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, tracking and scene change detection. 

Collaborative mapping with AGV

Mapping and navigation with AGV in industrial environments is happening now. Are you part of it? 

If you are willing to work on this R&D topic and you have background in the fields:

  • Computer science
  • Image processing
  • Robotics

you should contact one of the responsable persons.

SeaMap, a SeaClear support grant

SeaMap develops a coherent agenda of support technical activities that accelerate progress in the parent project SeaClear. We will develop mapping algorithms based on optimization, general and applicable to underwater litter mapping. Techniques will be created for processing 2D and 3D sensor data from the robots. Finally, support activities on interfacing and deployment of SeaClear algorithms on marine and aerial robots will be undertaken.

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:

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