Networked Robotics Laboratory (NeBoLab)
NeBoLab offers a platform for researchers and students to study and work with robotics experiment involving multiple and heterogeneous robotic systems.
NeBoLab currently consists of the following robotic systems:
- Mobile robots (6 TurtleBot3 Burger and 2 TurtleBot3 Waffle with manipulator)
- Quadcopters (10 Crazyflie 2.1 equipped with different decks and 1 Parrot Anafi drone)
- ZED 2 Stereo camera
- VICON motion capture cameras for global localization
IINES group is actively offering topics for courses (Robotics Project Work) and thesis (bachelor, master, doctoral levels) which utilize the experimental testbed in NeBoLab.
To interested students: If you have ideas/topics in mind for your bachelor or master thesis related to the (multi-)robot scenario and would like to discuss further/complete your thesis in our group, feel free to contact Azwirman Gusrialdi .
Note: This page will be updated regularly with the demos/results done by our students/researchers (stay tuned!)
Experiment/Simulation Results (Demos)
1. Potential field based obstacle avoidance experiments with crazyflies
- First experiment: the quadcopter has to fly to the specified goal position while avoiding static obstacles.
- Second experiment: two quadcopters have to exchange their positions while avoiding collision among themselves.
2. Resilient leader-following consensus experiments with turtlebots
- First experiment: all three robots have to meet at a common location (with biased introduced to avoid collision, at least in the final position) which is only known to the red robot. Here, the blue robot can receive information from the red robot while the green robot receives information from the blue robot. As can be seen, all the robots are able to meet at a common location using the standard leader-following consensus algorithm.
- Second experiment: we consider similar scenario as in the first experiment but now an adversary (attacker) is able to manipulate the information that the blue and green receive via the communication channel and also to insert injection into the actuator of the the blue and green robots. As can be observed, the blue and green robots are not able to meet at the specified location using the standard leader-following consensus algorithm.
- Third experiment: we consider similar scenario as in the second experiment but now we apply a novel resilient cooperative control algorithm. The resilient control guarantees all three robots to meet at the specified location in presence of unknown attacks.
3. Persistent monitoring with a network of quadrotors for indoor farming application
- In this simulation, a network of autonomous quadrotors persistently monitor the coverage holes generated by a number of broken static sensors in an indoor farming scenario.
4. Communication-efficient formation maintenance for multi-robot system with a safety certificate
We propose a novel cooperative control algorithm for coordinating multiple robots in achieving several control objectives (subtasks). To this end, we utilize control barrier function to describe the subtasks in combination with QP-based controller to provide a safety certificate. Moreover, a novel group collision avoidance algorithm is proposed to reduce the required communication between the robots.
- Scenario 1: A group of four robots need to go to a pre-defined goal position while maintaining their rigid formation and avoiding static obstacles along the way.
- Scenario 2: Two-robot formations need to go to the pre-defined goal positions while maintaining their rigid formation and avoiding collision with the other group formation.
