Taking advantage of symmetries: Gathering of many asynchronous oblivious robots on a ring

One of the recently considered models of robot-based computing makes use of identical, memoryless mobile units placed in nodes of an anonymous graph. The robots operate in Look–Compute–Move cycles; in one cycle, a robot takes a snapshot of the current configuration (Look), takes a decision whether to stay idle or to move to one of the nodes adjacent to its current position (Compute), and in the latter case makes an instantaneous move to this neighbor (Move). Cycles are performed asynchronously for each robot.In such a restricted scenario, we study the influence of symmetries of the robot configuration on the feasibility of certain computational tasks. More precisely, we deal with the problem of gathering all robots at one node of the graph, and propose a solution based on a symmetry-preserving strategy. When the considered graph is an undirected ring and the number of robots is sufficiently large (more than 18), such an approach is proved to solve the problem for all starting situations, as long as gathering is feasible. In this way we also close the open problem of characterizing symmetric situations on the ring which admit a gathering [R. Klasing, E. Markou, A. Pelc: Gathering asynchronous oblivious mobile robots in a ring, Theoret. Comput. Sci. 390 (1) (2008) 27–39].The proposed symmetry-preserving approach, which is complementary to symmetry-breaking techniques found in related work, appears to be new and may have further applications in robot-based computing.     

How many oblivious robots can explore a line

We consider the problem of exploring an anonymous line by a team of k identical, oblivious, asynchronous deterministic mobile robots that can view the environment but cannot communicate. We completely characterize sizes of teams of robots capable of exploring an n-node line. For k<n, exploration by k robots turns out to be possible, if and only if either k=3, or k?5, or k=4 and n is odd. For all values of k for which exploration is possible, we give an exploration algorithm. For all others, we prove an impossibility result.     

Self-deployment of mobile sensors on a ring

Mobile sensors can self-deploy in a purely decentralized and distributed fashion, so as to reach in a finite time a state of static equilibrium in which they uniformly cover the environment. We consider the self-deployment problem in a ring (e.g., a circular rim); in particular we investigate under what conditions the problem is solvable by a collection of identical sensors without a global coordinate system, however capable of determining the location (in their local coordinate system) of the other sensors within a fixed distance (called visibility radius). A self-deployment is exact   if within finite time the distance between any two consecutive sensors along the ring is the same, d$d$; it is ?$?$-approximate   if within finite time the distance between two consecutive sensors is between d−?$d-?$ and d+?$d+?$.     

Global output-feedback path tracking of unicycle-type mobile robots

We present an output-feedback controller that forces the output (position and orientation) of a unicycle-type mobile robot to track a predefined path. A coordinate transformation is first derived to cancel the velocity quadratic terms. An observer is then designed to globally exponentially/asymptotically estimate the unmeasured velocities. The controller synthesis is based on Lyapunov's direct method and the backstepping technique. Our proposed controller works for both internally damped and un-damped cases. Simulations illustrate the soundness of the proposed controller.     

Autonomous mobile robots navigation using RBF neural compensator

This paper presents an approach to adaptive trajectory tracking of mobile robots which combines a feedback linearization based on a nominal model and a RBF-NN adaptive dynamic compensation. For a robot with uncertain dynamic parameters, two controllers are implemented separately: a kinematics controller and an inverse dynamics controller. The uncertainty in the nominal dynamics model is compensated by a neural adaptive feedback controller. The resulting adaptive controller is efficient and robust in the sense that it succeeds to achieve a good tracking performance with a small computational effort. The analysis of the RBF-NN approximation error on the control errors is included. Finally, the performance of the control system is verified through experiments.     

Optimality and competitiveness of exploring polygons by mobile robots

A mobile robot, represented by a point moving along a polygonal line in the plane, has to explore an unknown polygon and return to the starting point. The robot has a sensing area which can be a circle or a square centered at the robot. This area shifts while the robot moves inside the polygon, and at each point of its trajectory the robot “sees” (explores) all points for which the segment between the robot and the point is contained in the polygon and in the sensing area. We focus on two tasks: exploring the entire polygon and exploring only its boundary. We consider several scenarios: both shapes of the sensing area and the Manhattan and the Euclidean metrics.We focus on two quality benchmarks for exploration performance: optimality (the length of the trajectory of the robot is equal to that of the optimal robot knowing the polygon) and competitiveness (the length of the trajectory of the robot is at most a constant multiple of that of the optimal robot knowing the polygon). Most of our results concern rectilinear polygons. We show that optimal exploration is possible in only one scenario, that of exploring the boundary by a robot with square sensing area, starting at the boundary and using the Manhattan metric. For this case we give an optimal exploration algorithm, and in all other scenarios we prove impossibility of optimal exploration. For competitiveness the situation is more optimistic: we show a competitive exploration algorithm for rectilinear polygons whenever the sensing area is a square, for both tasks, regardless of the metric and of the starting point. Finally, we show a competitive exploration algorithm for arbitrary convex polygons, for both shapes of the sensing area, regardless of the metric and of the starting point.     

Vision-based formation control of mobile robots

1Introduction Formation control of multiple vehicles,such ascooperative control of a group of mobile robots[1~4]and multiple spacecraft[5,6],has beenrecognized as a keytechnologyfor the future and studied by many researchersin recent years.The various control approaches to multiplevehicle formation reported in the literature can becategorized into three groups:leader following schemes;behavior_based methods;and virtual structure techniques.In the leader following approach[1,2,7],one of thevehi…     

Detection of doors using a genetic visual fuzzy system for mobile robots

Doors are common objects in indoor environments and their detection can be used in robotic tasks such as map-building, navigation and positioning. This work presents a new approach to door-detection in indoor environments using computer vision. Doors are found in gray-level images by detecting the borders of their architraves. A variation of the Hough Transform is used in order to extract the segments in the image after applying the Canny edge detector. Features like length, direction, or distance between segments are used by a fuzzy system to analyze whether the relationship between them reveals the existence of doors. The system has been designed to detect rectangular doors typical of many indoor environments by the use of expert knowledge. Besides, a tuning mechanism based on a genetic algorithm is proposed to improve the performance of the system according to the particularities of the environment in which it is going to be employed. A large database of images containing doors of our building, seen from different angles and distances, has been created to test the performance of the system before and after the tuning process. The system has shown the ability to detect rectangular doors under heavy perspective deformations and it is fast enough to be used for real-time applications in a mobile robot.     

Vision-based formation control of mobile robots

In this paper,a formatio n control algorithm and an obstacle avoidance control algorithm for mobile robots are developed based on a relative motion sensory system such as a pan/tilt camera vision system,without the need for global sensing and communication between robots.This is achieved by e mploying the velocity variation,instead of actual ve locities,as the control inputs.Simulation and experi mental results have demonstrated the effectiveness of the proposed control methods.     

A new multisensor fusion SLAM approach for mobile robots

This paper presents a novel method, which enhances the use of external mechanisms by considering a multisensor system, composed of sonars and a CCD camera. Monocular vision provides redundant information about the location of the geometric entities detected by the sonar sensors. To reduce ambiguity significantly, an improved and more detailed sonar model is utilized. Moreover, Hough transform is used to extract features from raw sonar data and vision image. Information is fused at the level of features. This technique significantly improves the reliability and precision of the environment observations used for the simultaneous localization and map building problem for mobile robots. Experimental results validate the favorable performance of this approach.     

A novel trajectory-tracking control law for wheeled mobile robots

In this paper a novel kinematic model is proposed where the transformation between the robot posture and the system state is bijective. A nonlinear control law is constructed in the Lyapunov stability analysis framework. This control law achieves a global asymptotic stability of the system based on the usual requirements for reference velocities. The control law is extensively analysed and compared to some existing, globally stable control laws.     

Dynamic localization with hybrid trilateration for mobile robots in intelligent space

In this paper, we propose a new localization algorithm based on a hybrid trilateration algorithm for obtaining an accurate position of a robot in intelligent space. The proposed algorithm is also able to estimate a position of the moving robot by using the extended Kalman filter, taking into consideration time synchronization and velocity of the robot. For realizing the localization system, we employ several smart sensors as beacons on the ceiling in intelligent space and as a listener attached to the robot. Finally, simulation results show the feasibility and effectiveness of the proposed localization algorithm compared with existing trilateration algorithms.     

Semiglobal practical stabilization of nonholonomic wheeled mobile robots with saturated inputs

In the practical design of nonholonomic control systems, saturated input is an important issue to consider. A number of stabilizing controllers for chained forms with bounded inputs have been proposed by different researchers. Under some conditions, nonholonomic wheeled mobile robots (NWMR) can be transformed into chained forms by state and input transformations. In this paper, we propose semiglobal practical stabilizing control schemes for a class of NWMR with saturated inputs. These schemes are given not based on chained forms, but based on a kind of new systems which are converted from NWMR by using state transformations without any input transformation. The advantage for doing this is involved in two points: first, the stabilizers proposed are semiglobal. Second, for the methods exploited here, the original system inputs (in the sense of kinematics) can be guaranteed to stay within the desired upper bounds. Finally, the simulation is given.     

Optimal solutions to a class of power management problems in mobile robots

This paper studies an approach to minimize the power consumption of a mobile robot by controlling its traveling speed and the frequency of its on-board processor simultaneously. The problem is formulated as a discrete-time optimal control problem with a random terminal time and probabilistic state constraints. A general solution procedure suitable for arbitrary power functions of the motor and the processor is proposed. Furthermore, for a class of realistic power functions, the optimal solution is derived analytically. Interpretations of the optimal solution in the practical context are also discussed. Simulation results show that the proposed method can save a significant amount of energy compared with some heuristic schemes.     

An effective posture stabilizer for differential drive mobile robots

A continuous time-invariant feedback controller for differential drive mobile robots is proposed. Its main contribution is to stabilize a differential drive mobile robot to a desired posture through only smooth trajectory without inversion of the drive direction. Experimental results are reported to show the validity of the controller.     

Behavior patterns emerging among mobile robots with a diversity of personalities cooperating in collection and cleaning-up tasks

We investigated the behavior patterns emerging among autonomous mobile robots with diverse personalities. They cooperate with one another in collection and cleaning-up tasks. First, we emphasize the rationale for introducing personalities into robots. Second, we present our assumptions on the common functions of the robots, i.e., visual functions, mobility, and the capturing and conveying of target objects. Third, we define a function which is specific to each robot; its personality. Fourth, we explain the collision avoidance behavior, which is very dependent on the personalities. Finally, we present the results of simulation studies of robots with diverse personalities cooperating in collection and cleaning-up tasks. We discuss the influence of the distribution of various personalities on the performance of the tasks. This work was presented in part at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, January 15–17, 2001     

Gathering few fat mobile robots in the plane

Autonomous identical robots represented by unit discs move deterministically in the plane. They do not have any common coordinate system, do not communicate, do not have memory of the past and are totally asynchronous. Gathering such robots means forming a configuration for which the union of all discs representing them is connected. We solve the gathering problem for at most four robots. This is the first algorithmic result on gathering robots represented by two-dimensional figures rather than points in the plain: we call such robots fat.     

Navigation of multiple mobile robots in a highly clutter terrains using adaptive neuro-fuzzy inference system

In recent years, the interest in research on robots has increased extensively; mainly due to avoid human to involve in hazardous task, automation of Industries, Defence, Medical and other household applications. Different kinds of robots and different techniques are used for different applications. In the current research proposes the Adaptive Neuro Fuzzy Inference System (ANFIS) Controller for navigation of single as well as multiple mobile robots in highly cluttered environment. In this research it has tried to design a control system which will be able decide its own path in all environmental conditions to reach the target efficiently. Some other requirement for the mobile robot is to perform behaviours like obstacle avoidance, target seeking, speed controlling, knowing the map of the unknown environments, sensing different objects and sensor-based navigation in robot’s environment.     

Vision-based global localization for mobile robots with hybrid maps of objects and spatial layouts

This paper presents a novel vision-based global localization that uses hybrid maps of objects and spatial layouts. We model indoor environments with a stereo camera using the following visual cues: local invariant features for object recognition and their 3D positions for object pose estimation. We also use the depth information at the horizontal centerline of image where the optical axis passes through, which is similar to the data from a 2D laser range finder. This allows us to build our topological node that is composed of a horizontal depth map and an object location map. The horizontal depth map describes the explicit spatial layout of each local space and provides metric information to compute the spatial relationships between adjacent spaces, while the object location map contains the pose information of objects found in each local space and the visual features for object recognition. Based on this map representation, we suggest a coarse-to-fine strategy for global localization. The coarse pose is estimated by means of object recognition and SVD-based point cloud fitting, and then is refined by stochastic scan matching. Experimental results show that our approaches can be used for an effective vision-based map representation as well as for global localization methods.