Trajectory planning of autonomous heterogeneous robots for cooperative 3D mapping of an unknown environment

• Grant number: 18/13848-1
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: October 01, 2018
• End date: December 31, 2022
• Field of knowledge: Engineering - Electrical Engineering
• Principal Investigator: Marco Henrique Terra
• Grantee: Kenny Anderson Queiroz Caldas
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

Autonomous mobile robots are increasingly performing activities previously performed by humans, especially risky, exhaustive or repetitive tasks. However, in many cases robots do not have a map of the work environment in advance, which requires them to be able to self locate and map their surroundings, simultaneously. This doctoral project proposes the safe navigation of heterogeneous robots for 3D mapping of an unknown environment. The need of multi-robots is due the reduction of the time of the mapping task and the possibility of combining different capacities of perception and locomotion. The data collection for localization and mapping will be performed by a Visual-inertial SLAM. A Robust Kalman Filter will be developed to select the best mode of operation of the navigation system, according to the availability and reliability of the sensors and the uncertainties present in the place where the robot is located. Based on integration of data from different sensors, the OctoMap framework will be used to obtain a robust and realistic volumetric model of the environment. A trajectory planner based on Bayesian optimization for multi-robot coordination will also be developed, aiming to search for areas where data collection will be maximized, while respecting the robots constraints. The algorithms will initially be developed and simulated in the Gazebo, an open source simulator that allows rapid prototyping of the system. To validate the methods developed in simulation, experiments will be carried out in the Center of Robotics of USP São Carlos, using Vicon's high precision motion capture system, which will serve as ground truth for the obtained results. The Laboratory of Intelligent Systems already has the mobile robots that will be used in the project for its Implementation.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CALDAS, KENNY A. Q.; INOUE, ROBERTO S.; TERRA, MARCO H.; IEEE. Commercial MAV Velocity Estimation Using Gaussian Process Regression for Drift Reduction. 2022 IEEE SENSORS, v. N/A, p. 4-pg., 2022-01-01. (14/50851-0, 18/13848-1)

BENEVIDES, JOAO R. S.; PAIVA, MARLON A. D.; SIMPLICIO, PAULO V. G.; INOUE, ROBERTO S.; TERRA, MARCO H.. isturbance Observer-Based Robust Control of a Quadrotor Subject to Parametric Uncertainties and Wind Disturbanc. IEEE ACCESS, v. 10, p. 7554-7565, 2022. (18/13848-1, 17/05668-0, 14/50851-0)

CALDAS, KENNY A. Q.; BENEVIDES, JOAO R. S.; INOUE, ROBERTO S.; TERRA, MARCO H.; IEEE. Autonomous Robust Navigation System for MAV Based on Monocular Cameras. 2022 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS), v. N/A, p. 7-pg., 2022-01-01. (14/50851-0, 18/13848-1, 17/05668-0)