Mobile Robotics LaboratoryInstitute of Systems and Robotics

ISR – Coimbra

• Aim

– Take advantage from intelligent cooperation between mobile robots, so as to build fast and accurate 3-D maps of unknown environments, through efficient information sharing based on information utility.

• A multi-robot system may be more efficient, reliable and robust than a single robot solution.

• The space and time distribution of multiple robots allow them to accomplish the mapping mission in less time.

• If there is an overlap in individual robots capabilities (redundancy), the failure of any particular robot does not compromise the overall mission accomplishment.

• It robots with different, complementary and specialized skills are used, they may overcome their individual limitations (e.g. different sensors, locomotion, etc.) and increase the system’s robustness.

• Background

– Some authors have already addressed the problem, though there are important limitations that we intend to overcome:

• Most approaches are restricted to 2-D indoor, flat maps and use a single robot;

• There are some probabilistic approaches (e.g. occupancy grids), but do not minimize inter-robot communication when fusing the maps from different robots;

• Very few authors used entropy to formulate the expected information gain of control actions – focused on coordination or not viable in real-time.

• Studies about multi-robot communication focus mainly on the communication structure rather than on the communication contents.

• They are tailored in indoor and flat environments; our approach is aimed at using a team of cooperating mobile robots to build 3-D coverage maps of environments not necessarily flat.

– There is no a principled mechanism to assess information utility, which might be used to support efficient multi-robot communication.

• Using efficiently communication resources is crucial to scale up MRS for teams of many robots.

• Research issues

– Grid-based probabilistic maps [3]

• The occupancy of each cell – voxel – is modeled through a continuous random variable, ranging from empty cell to fully occupied voxel.

• Compact representation: only two parameters are stored for each voxel.

• Explicit representation of uncertainty through the entropy concept.

• Straightforward update of the voxel’s coverage belief through a Bayes Filter.

– Entropy gradient-based exploration [3]

• Reformulation of frontier-based exploration: frontier voxels have maximum entropy gradient.

– Distributed architecture model [1]

• Each robot is capable of building a 3-D map, though it is altruistically committed to share useful measurements with its teammates, who also may provide it with useful data.

– Entropy-based measure of information utility [1]

• Used to support efficient information sharing.

• Sensory data is as useful as it contributes to improve the robot’s map.

– Coordinated exploration based on the minimization of mutual information [2]

• Each robot avoids to sense regions that are already being sensed by other robots.

• Minimize robots’ interference: partial occlusions and not reachable exploration viewpoints.

• Selected publications[1] R. Rocha, J. Dias and A. Carvalho. Cooperative multi-robot systems: a study of vision-based 3-D mapping

using information theory. In Proc. of Int. Conf. on Robotics and Automation (ICRA’2005), Barcelona, Spain, pages 386-391, Apr. 2005.

[2] R. Rocha, J. Dias and A. Carvalho. Entropy gradient-based exploration with cooperative robots in 3-D mapping missions. In Proc. of ICRA’2005 Workshop on Cooperative Robotics, IEEE Int. Conf. on Robotics and Automation, Barcelona, Spain, Apr. 2005.

[3] R. Rocha, J. Dias, and A. Carvalho. Exploring Information Theory for Vision-Based Volumetric Mapping. In Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS’2005), Edmonton, Canada, pages 2409-2414, 2-6 Aug. 2005.

Cooperative Multi-Robot SystemsVision-based 3-D Mapping using Information Theory

Contact Person:Rui RochaEmail: rprocha@isr.uc.pt

Rui Rocha, M.Sc., Jorge Dias, Ph.D., Adriano Carvalho, Ph.D.

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