ROBOSAT
Autonomous robot navigation in the wild using satellite-based 3D geographical information
About ROBOSAT
Massive collection of multidimensional satellite-based 3D geographic information systems (GIS) is now a reality. Yet the correlation of such data with local information, especially in unconstrained environments such as in the wild, is a poorly addressed challenge so far.
Our project aims to provide a scalable MultiGIS high-quality data collection platform through the use of a quadrupedal robot that can autonomously perform long-distance missions in challenging environments. Our project will also develop general-purpose and automatic tools for multi-sensor data storage, data management, data consolidation, and data labelling based on Artificial Intelligence (AI) / Machine Learning (ML) algorithms and will look into solutions for efficient data use and dissemination.
This project will lay the foundations for ubiquitous robots in the wild as well as for a MultiGIS database for unstructured environments that is to be an order of magnitude larger than any of the currently existing ones.
Work Packages
The ROBOSAT activities are grouped in five work packages (WPs):
- WP1 – Management, dissemination, open science, communication and exploitation;
- WP2 – Developing robot and sensor solutions for high-quality data gathering;
- WP3 – Solutions for more precise and robust GNSS localization algorithms;
- WP4 – Novel large-scale open-access data with automatic labelling;
- WP5 – Field deployments and data collection.
Objectives
- Develop a quadrupedal robot and a sensor payload for scalable autonomous data collection in the wild.
- Provide increased accuracy and robustness of GNSS algorithms using MultiGIS data fusion.
- Offer novel large-scale open-access MultiGIS data with automatic labelling.
Funding
In Romania, ROBOSAT is co-funded by the National Executive Agency for Higher Education, Research, Development and Innovation Funding – UEFISCDI and the CHIST-ERA program.
Results
Phase I
Activity 1.1: Analysis of ethical issues related to AI usage and correlated with the project implementation - part 1: The analysis of the ethical issues related to exploring the environment with an autonomous robot and collecting a large set of information such as images, videos, coordinates, etc. revealed the importance of the following elements: (a) confidentiality and protection of geospatial data; (b) robotic autonomy and decision-making responsibility; (c) bias in labeling and data fusion algorithms; (d) environmental impact and the ethics of interacting with nature; (e) the ethics of disseminating and reusing collected data.
Activity 1.2: Identifying hardware solutions for the robotic platform: Mobile robots that operate autonomously in complex and unstructured environments require an ansamble of multimodal sensors capable of capturing diverse and complementary information. Designing such a suite of sensors involves multiple critical design decisions, such as sensor selection, component placement, power limitations, computing requirements, communication, synchronization, and calibration.
In terms of positioning, GNSS receivers typically accept single-antenna or dual-antenna configurations; the latter not only provides improved positioning accuracy but also direction estimation. The choice of antennas and receiver capabilities dictates which satellite constellations can be used. In terms of robustness in real environments and on rough terrain, the sensor system must be designed to be robust. It must withstand occasional drops and impacts during operation in various weather conditions throughout all seasons and must be dust and water resistant, in accordance with the IP65 standard. In terms of energy autonomy, the aim is for the sensor suite to consume no more than 300 W so that autonomy of several hours can be achieved by powering it from a medium-capacity battery. In terms of sensors and perception systems, it is important to equip the robot with perception sensors which have to optimize weight, performance and placement.
Activity 1.3: Analysis of suitable simulation environments for robotic platforms: During this stage, several simulation environments for robotic platforms were identified and analyzed. Each simulator analyzed has specific strengths that make it suitable for certain types of applications. Gazebo is preferred in academic and industrial projects involving ROS. Webots is excellent for beginners and prototyping. CoppeliaSim is ideal for complex industrial simulations and multi-robot scenarios. Isaac Sim is suitable for advanced AI applications and simulations with high graphics requirements. The Construct is a good choice for learning, training, and rapid testing in ROS environments without complicated configurations.
Activity 1.4: Widespread scientific dissemination of results (website, social media): As part of this activity, the ROBOSAT project website was developed and can be viewed at the following address: https://citst.ro/projects/robosat. The project is also present on LinkedIn: https://www.linkedin.com/showcase/108599174/admin/dashboard/.
Contact Us
Address
IT Centre for Science and Technology
Av. Radu Beller, No. 25, Sect. 1, Bucharest, Romania