The gathering problem of anonymous and oblivious mobile robots is one of the fundamental problems in the theoretical mobile robotics. We consider the gathering problem in unoriented and anonymous rings, which requires that all robots eventually keep their positions at a common non-predefined node. Since the gathering problem cannot be solved without any additional capability to robots, all the previous results assume some capability of robots, such as the agreement of local view. In this paper, we focus on the multiplicity detection capability. This paper presents a deterministic gathering algorithm with local-weak multiplicity detection, which provides a robot with information about whether its current node has more than one robot or not. This assumption is strictly weaker than that in previous works. Our algorithm achieves the gathering from an aperiodic and asymmetric configuration with 2 < k < n/2 robots, where n is the number of nodes. We also show that our algorithm is asymptotically time-optimal one, i.e., the time complexity of our algorithm is O(n). Interestingly, despite the weaker assumption, it achieves significant improvement compared to the previous algorithm, which takes O(kn) time for k robots.

Obtaining a compact representation of a large-size feature map built by mapper robots is a critical issue in recent mobile robotics. This “map compression” problem is explored from a novel perspective of dictionary-based data compression techniques in the paper. The primary contribution of the paper is the proposal of the dictionary-based map compression approach. A map compression system is presented by employing RANSAC map matching and sparse coding as building blocks. The effectiveness levels of the proposed techniques is investigated in terms of map compression ratio, compression speed, the retrieval performance of compressed/decompressed maps, as well as applications to the Kolmogorov complexity.

In this paper, we study the decentralized coverage control problem for an environment using a group of autonomous mobile robots with nonholonomic kinematic and dynamic constraints. In comparison with standard coverage control procedures, we develop a combined controller for Voronoi-based coverage approach in which kinematic and dynamic constraints of the actual mobile sensing robots are incorporated into the controller design. Furthermore, a collision avoidance component is added in the kinematic controller in order to guarantee a collision free coverage of the area. The convergence of the network to the optimal sensing configuration is proven with a Lyapunov-type analysis. Numerical simulations are provided approving the effectiveness of the proposed method through several experimental scenarios.

An adaptive backstepping and high order sliding modes control algorithm is proposed for output tracking of mobile robots. The controller can greatly reduce the chattering due to conventional sliding modes technique. The proposed algorithm has certain robustness with respect to the external random disturbances and good adaptability with respect to the parametric uncertainty. The effectiveness of the proposed control strategy is demonstrated by simulations studies.

A computed torque controller for a dynamic model of nonholonomic mobile robots with bounded external disturbance is proposed to treat the adaptive tracking control problem using the separated design method. A velocity controller is first designed for the kinematic steering system to make the tracking error approaching to zero asympotically. Then, a computed torque controller is designed such that the true mobile robot velocity converges to the desired velocity controller. In each step, the controllers are designed independently, and this will simplify the design of controllers. A novel stability analysis involving the estimation of some differential inequalities is also given to guarantee the stability of the closed-loop system. Moreover, the regulation problem and the tracking problem will be treated using the proposed controller. In particular, the mobile robots can globally follow any path such as a straight-line, a circle and the path approaching to the origin. Furthermore, the problems of back-into-garage parking and the parallel parking problem can also be solved using the proposed controller. Some interesting simulation results are given to illustrate the effectiveness of the proposed tracking control law.

This paper addresses a high-order sliding mode control strategy for output tracking of nonholonomic mobile robots. First, we introduce the dynamic model of robots, driving motors and nonslipping kinematics constraint conditions. Second, we decompose the system into linear and nonlinear components via diffeomorphism and nonlinear input transformation. Also we consider parameter variations of robots and deduce the uncertain model of robots. Third, we design a high order sliding mode controller for output tracking of known and uncertain systems, respectively. Finally, we perform numerical simulations, demonstrating that the proposed high-order sliding mode control not only reduces the chattering problem of sliding mode systems, but also has certain robustness properties with respect to uncertainties of robots.

A general tracking control problem for mobile robots is proposed and solved using the backstepping technique. A global result is given for the kinematic steering system to make the tracking error approaching to zero asymptotically. Based on our efforts, the proposed controller can solve both the tracking problem and the regulation problem of mobile robots. In particular, mobile robots can now globally follow any differentiable with bounded velocities path such as a straight line, a circle and the path approaching to the origin using the proposed controller. Moreover, the problem of back-into-garage parking is also solved by our approach. Some interesting simulation results are given to illustrate the effectiveness of the proposed tracking control laws.

This paper proposes genetic algorithms (GAs) for path planning and trajectory planning of an autonomous mobile robot. Our GA-based approach has an advantage of adaptivity such that the GAs work even if an environment is time-varying or unknown. Therefore, it is suitable for both off-line and on-line motion planning. We first presents a GA for path planning in a 2D terrain. Simulation results on the performance and adaptivity of the GA on randomly generated terrains are shown. Then, we discuss an extension of the GA for solving both path planning and trajectory planning simultaneously.

In this paper, we propose the distributed stable marriage problem and apply it to planning for cooperative works of autonomous mobile robots and battery charger stations. We develop and analyze a distributed algorithm to determine the partner by message communication.