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Autonomous Multi-robot Exploration of Partially Unknown Environments
The goal of this project is to implement a multi-robot path-planning strategy in order to perform autonomous navigation and exploration of a partially unknown environment by employing a team of robots.
Keywords: Path Planning, Exploration, Multi-robot, Information Gathering, SLAM, Autonomous Navigation
In the recent years, the use of robotic platforms has increased exponentially to a wide range of different settings and situations, such as mapping and inspection. In order to enable robots to navigate in complex, unknown and dynamic environments, they must be able to ***move with guaranteed safety***, even when facing environments they do not have full prior knowledge of. However, the ***full autonomous navigation*** still remains a big challenge.
The aim of this project is to develop a ***multi-robot planner*** that allows autonomous exploration of partially unknown environments using a robotic team. The objective is to cover the whole area of interest in the shortest time possible, while coordinating the motions of the agents in the team. The path planner should be able to run online and coordinate the motions to avoid collisions among the agents and between the agents and the environment. The goals are the following:
- Implementation of a multi-robot path-planning strategy.
- Evaluation of the algorithm against other state-of-the-art planners.
- Use of the planner for the navigation of a team of real ground robots (Super Mega Bot).
In the recent years, the use of robotic platforms has increased exponentially to a wide range of different settings and situations, such as mapping and inspection. In order to enable robots to navigate in complex, unknown and dynamic environments, they must be able to ***move with guaranteed safety***, even when facing environments they do not have full prior knowledge of. However, the ***full autonomous navigation*** still remains a big challenge.
The aim of this project is to develop a ***multi-robot planner*** that allows autonomous exploration of partially unknown environments using a robotic team. The objective is to cover the whole area of interest in the shortest time possible, while coordinating the motions of the agents in the team. The path planner should be able to run online and coordinate the motions to avoid collisions among the agents and between the agents and the environment. The goals are the following: - Implementation of a multi-robot path-planning strategy. - Evaluation of the algorithm against other state-of-the-art planners. - Use of the planner for the navigation of a team of real ground robots (Super Mega Bot).
- ***WP1***: Familiarization with state-of-the-art literature on the multi-robot path-planning problem.
- ***WP2***: Implementation of a multi-robot path-planning strategy.
- ***WP3***: Evaluation of the new framework with respect to other already existing strategies.
- ***WP4***: Design and conduct experiments with a team of ground robots.
- ***WP1***: Familiarization with state-of-the-art literature on the multi-robot path-planning problem. - ***WP2***: Implementation of a multi-robot path-planning strategy. - ***WP3***: Evaluation of the new framework with respect to other already existing strategies. - ***WP4***: Design and conduct experiments with a team of ground robots.
- Interest in Computer Sciences, Robotics and Autonomous Navigation;
- C++ programming experience;
- Experience in mobile robotics, Linux, ROS is beneficial.
- Interest in Computer Sciences, Robotics and Autonomous Navigation; - C++ programming experience; - Experience in mobile robotics, Linux, ROS is beneficial.
Interested Students please send CV, Bachelor and Master transcripts to Luca Bartolomei (lbartolomei@ethz.ch). **Do not** apply on Sirop.
Interested Students please send CV, Bachelor and Master transcripts to Luca Bartolomei (lbartolomei@ethz.ch). **Do not** apply on Sirop.