Abstract:In this paper, we present a novel solution for a path following problem in partially-known static environments. Given linearized error dynamic equations, model predictive control (MPC) is employed to produce a sequence of angular velocities. Since the forward velocity of the robot has to be adapted to environmental constraints and robot dynamics while the robot is following a path, we propose an optimal solution to generate the velocity profile. Furthermore, we integrate an obstacle-avoidance behavior using local sensor information with a path-following behavior based on global knowledge. To achieve this, we introduce new waypoints in order to move the robot away from obstacles while the robot still keeps following the desired path. Extensive simulations and experiments with a physical unicycle mobile robot have been conducted to illustrate the effectiveness of our path following control framework.

Abstract-Mapping is regarded as one of the most fundamental tasks for mobile robots. In this work, we present an approach that enables multiple resource-limited mobile robots to cooperatively build an image-based map of the environment and to afterwards localize in it. To achieve this, we deploy a hierarchical team of mobile robots. A parent robot possesses state-of-the-art sensors, computation power and acts as a leader. It teleoperates small child robots within its line-of-sight. In contrast to other approaches and due to the cooperation among the robots, we can relax the requirement that every robot must be able to self-localize to take part in multi-robot mapping. Additionally, our algorithm ensures the mapping of the entire area in an efficient way, i.e., it fulfills the requirements of area coverage. To test our approach, extensive experiments have been performed both in simulation and real-world. In the latter case, a team of four heterogeneous mobile robots was deployed. Besides the successful cooperation in the robot team, localization results are presented to validate the applicability of the proposed mapping procedure.

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Abstract. A control strategy for coordinated path following of multiple mobile robots is presented in this paper. A virtual vehicle concept is combined with a path following approach to achieve formation tasks. Our formation controller is proposed for the kinematic model of unicycle-type mobile robots. It is designed in such a way that the path derivative is employed as an additional control input to synchronize the robot's motion with neighboring robots. A second-order consensus algorithm under undirected information exchange is introduced to derive the control law for synchronization. Our controller was validated by simulations and experiments with three unicycle-type mobile robots.

In this paper, we present a novel approach to the area coverage problem by using a team of heterogeneous mobile robots. In our method, a parent robot is assumed to possess state-of-the-art sensors and sufficient computation power to establish robust localization and navigation. A large number of inexpensive and small child robots possess only restricted sensing and computation capabilities. They can only fulfill a certain task, e.g., floor-cleaning, but can be teleoperated in line-of-sight of the parent robot. To exploit the advantages of both types of robots, the team cooperatively covers the area in an efficient way. In contrast to other approaches and due to the cooperation of the robots, we can relax the requirement that every robot must be able to self-localize and robustly navigate to take part in efficient multi-robot coverage. Simulation results are presented in which our approach was tested intensively.