In the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper.

https://journals.sagepub.com/doi/pdf/10.5772/57313

A Survey and Analysis of Multi-Robot Coordination

Autonomous vehicles are expected to play a key role in the future of urban transportation systems, as they offer potential for additional safety, increased productivity, greater accessibility, better road efﬁciency, and positive impact on the environment. Research in autonomous systems has seen dramatic advances in recent years, due to the increases in available computing power and reduced cost in sensing and computing technologies, resulting in maturing technological readiness level of fully autonomous vehicles. The objective of this paper is to provide a general overview of the recent developments in the realm of autonomous vehicle software systems. Fundamental components of autonomous vehicle software are reviewed, and recent developments in each area are discussed.

Perception, Planning, Control, and Coordination for Autonomous Vehicles

Research Advance in Swarm Robotics

This paper presents a framework for collaborative localization and mapping with multiple Micro Aerial Vehicles (MAVs) in unknown environments. Each MAV estimates its motion individually using an onboard, monocular visual odometry algorithm. The system of MAVs acts as a distributed preprocessor that streams only features of selected keyframes and relative-pose estimates to a centralized ground station. The ground station creates an individual map for each MAV and merges them together whenever it detects overlaps. This allows the MAVs to express their position in a common, global coordinate frame. The key to real-time performance is the design of data-structures and processes that allow multiple threads to concurrently read and modify the same map. The presented framework is tested in both indoor and outdoor environments with up to three MAVs. To the best of our knowledge, this is the first work on real-time collaborative monocular SLAM, which has also been applied to MAVs.

http://vigir.missouri.edu/~gdesouza/Research/Conference_CDs/IEEE_IROS_2013/media/files/1342.pdf

Collaborative monocular SLAM with multiple Micro Aerial Vehicles

/pdf/ccm-slam-robust-and-efficient-centralized-collaborative-1k0x60c975.pdf

CCM-SLAM: Robust and efficient centralized collaborative monocular simultaneous localization and mapping for robotic teams

In this paper we consider the problem of simultaneously localizing all members of a team of robots. Each robot is equipped with proprioceptive sensors and exteroceptive sensors. The latter provide relative observations between the robots. Proprioceptive and exteroceptive data are fused with an Extended Kalman Filter. We derive the equations for this estimator for the most general relative observation between two robots. Then we consider three special cases of relative observations and we present the structure of the filter for each case. Finally, we study the performance of the approach through many accurate simulations.

/pdf/multi-robot-localization-using-relative-observations-1nbvpas03b.pdf

Multi-Robot Localization Using Relative Observations

Reference LSA-CONF-2005-034 Conference Web Site: http://wwwm2vipcom/ Record created on 2006-12-07, modified on 2016-08-08

Model-Based Relative Localization for Cooperative Robots Using Stereo Vision

We introduce an initial implementation of a real-time component-based software framework for autonomous mobile robots. We argue that real-world autonomous mobile robots shall be controlled by self-contained software systems able to meet hard timing constraints. The proposed solution empowers specialized roboticists to contribute software components that can be integrated into complete real-time systems. The framework also facilitates robotic software components reuse and portability across hardware platforms. Based on an indoor navigation case study we evaluate the advantages and the limitations of the framework in terms of ease of use, modularity and real-time capabilities.

/pdf/a-real-time-software-framework-for-indoor-navigation-4bmmm1trun.pdf

A real-time software framework for indoor navigation

Reference LSA-CONF-2005-011View record in Web of Science Conference Web Site: http://www.aim2005.mtu.edu/ Record created on 2006-12-07, modified on 2016-08-08

Applications of a Real-Time Software Framework for Complex Mechatronic Systems

As the complexity of the missions to be performed by mechatronic systems grows, so does the amount of embedded software to be produced and the number of involved specialists. System complexity management and software integration become more important. In this paper, we present an initial implementation of a real-time capable software framework for complex mechatronic systems that facilitates embedded software development and integration. The framework also promotes software components reuse across applications, architecture reuse and software portability across hardware platforms. To illustrate the proposed solution, we present two applications of the framework: an autonomous indoor navigation system for mobile robots and a driver assistance system for smart cars

/pdf/applications-of-a-real-time-software-framework-for-complex-420t7owkgw.pdf

F. Pont

Papers

Multi-Robot Localization Using Relative Observations

Model-Based Relative Localization for Cooperative Robots Using Stereo Vision

A real-time software framework for indoor navigation

Applications of a Real-Time Software Framework for Complex Mechatronic Systems

Applications of a real-time software framework for complex mechatronic systems