This paper proposes a method for the visual-based navigation of a mobile robot in indoor environments, using a single omni-directional (catadioptric) camera. The geometry of the catadioptric sensor and the method used to obtain a bird's eye (orthographic) view of the ground plane are presented. This representation significantly simplifies the so to navigation protiok by eliminating any perspective effects. The nature of each navigation task is taken into account when designing the required navigation skills and environmental representation. We propose two main navigation mo dalities: Topological Navigation and Visual Path Following. To po lok Navigatio is used fo traveling lo distances and do es no require knowledge of the exact position of the robot but rather, a qualitative position of the took map. The navigation process combines appearance based methods and visual servorv up oso environmental features. Visual Path Following is required for local, very precise navigation fo e.g.do o traversal,do cking. The robot is contro to fo w a pre-specified p...

We describe a method for visual based robot navigation with a single omni-directional (catadioptric) camera. We show how omni-directional images can be used to generate the representations needed for two main navigation modalities: Topological Navigation and Visual Path Following. Topological Navigation relies on the robot’s qualitative global position, estimated from a set of omni-directional images obtained during a training stage (compressed using PCA). To deal with illumination changes, an eigenspace approximation to the Hausdorff measure is exploited. We present a method to transform omni-directional images to Bird’s Eye Views that correspond to scaled orthographic views of the ground plane. These images are used to locally control the orientation of the robot, through visual servoing. Visual Path Following is used to accurately control the robot along a prescribed trajectory, by using bird’s eye views to track landmarks on the ground plane. Due to the simplified geometry of these images, the robot’s pose can be estimated easily and used for accurate trajectory following. Omni-directional images facilitate landmark based navigation, since landmarks remain visible in all images, as opposed to a small field-of-view standard camera. Also, omni-directional images provide the means of having adequate representations to support both accurate or qualitative navigation. Results are described in the paper. 1.

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The subject of this paper is the motion control problem of wheeled mobile robots (WMRs) in environments without obstacles. With reference to the popular unicycle kinematics, it is shown that dynamic feedback linearization is an efficient design tool leading to a solution simultaneously valid for both trajectory tracking and setpoint regulation problems. The implementation of this approach on the laboratory prototype SuperMARIO, a two-wheel differentially driven mobile robot, is described in detail. To assess the quality of the proposed controller, we compare its performance with that of several existing control techniques in a number of experiments. The obtained results provide useful guidelines for WMR control designers.

In this paper we describe the use of a catadioptric panoramic system, built with a spherical mirror, for navigation tasks, namely visual path following. We define Visual Path Following as a method whereby once a robot has arrived at the start of a previously specified path, it can perform path following to a given location relying on visual tracking of features (landmarks) alone. The geometry of the catadioptric sensor and the method of image unwarping to obtain a bird's eye view of the ground plane are presented. The ground unwarp representation significantly simplifies the solution to navigational problems, since the image coordinates differ from ground coordinates by a simple scale factor, thus eliminating any perspective effects. Preliminary experiments with a mobile robot equiped with the described catadioptric panoramic sensor are detailed. Finally, encouraging and promising results obtained are presented. 1 Introduction Many real world mobile robot applications, such as home ...

We address the problem of position trajectorytracking and path-following control design for underactuated autonomous vehicles in the presence of possibly large modeling parametric uncertainty. For a general class of vehicles moving in either two or three-dimensional space, we demonstrate how adaptive switching supervisory control can be combined with a nonlinear Lyapunov-based tracking control law to solve the problem of global boundedness and convergence of the position tracking error to a neighborhood of the origin that can be made arbitrarily small. The desired trajectory does not need to be of a particular type (e.g., trimming trajectories) and can be any sufficiently smooth bounded curve parameterized by time. We also show how these results can be applied to solve the path-following problem, in which the vehicle is required to converge to and follow a path, without a specific temporal specification. We illustrate our design procedures through two vehicle control applications: a hovercraft (moving on a planar surface) and an underwater vehicle (moving in three-dimensional space). Simulations results are presented and discussed.

. A nonlinear control law to steer the unicycle model to a static or dynamic target pose is presented. If the target is static the control signals are smooth in their arguments and the solution guarantees exponential convergence of the distance and orientation errors to zero. The major advantages of the proposed approach are that there is no need for path planning and, in principle, there is no need for global selflocalization either. 1

B Biographical Sketch .................................135 viii List of Tables Table 1 Algorithm for path construction. .......................41 Table 2 Algorithm for determining the next movement direction. . . . . ....41 Table 3 Computational complexity of the system. . . ...............99 ix List of Figures Figure 1 Several mobile robots of the class we consider in the thesis. .... 9 Figure 2 The concept of a neural map. . .......................20 Figure 3 Self-organization at the neural mapping (9) level. More neurons are assigned to the `important' areas of X. The mapping is shown by superimposing the neural field F on the signal space X. . . . . . 24 Figure 4 The basic nonlinear processing unit or neuron. . . ...........25 Figure 5 The architecture of the subsystem for path planning with neural maps. ...................................... 31 Figure 6 Different network topologies and connections for 2-dimensional uniform coverage. . ..............................32 Figure 7 Connection weight as a function of distance. . . . ...........33 Figure 8 The nonlinear activation function. . . . ...................35 Figure 9 The target and obstacle configurations (left) and the contours of the equilibrium surface (right). . . . . ...................38 Figure 10 Network equilibrium state of a 50 50 neural map for a single target. ......................................39 Figure 11 The target and obstacle configurations (left) and the contours of the equilibrium surface (right). . . . . ...................39 Figure 12 Network equilibrium state of a 50 50 neural map for multiple targets. ......................................40 Figure 13 Update rasters on a 2-dimensional lattice. . ...............46 Fi...

The goal of this chapter is to provide tools for analyzing and controlling nonholonomic mechanical systems. This classical subject has received renewed attention because nonholonomic constraints arise in many advanced robotic structures, such as mobile robots, space manipulators, and multifingered robot hands. Nonholonomic behavior in robotic systems is particularly interesting, because it implies that the mechanism can be completely controlled with a reduced number of actuators. On the other hand, both planning and control are much more difficult than in conventional holonomic systems, and require special techniques. We show first that the nonholonomy of kinematic constraints in mechanical systems is equivalent to the controllability of an associated control system, so that integrability conditions may be sought by exploiting concepts from nonlinear control theory. Basic tools for the analysis and stabilization of nonlinear control systems are reviewed and used to obtain conditions for partial or complete nonholonomy, so as to devise a classification of nonholonomic systems. Several kinematic models of nonholonomic systems are presented, including examples of wheeled mobile robots, free-floating space structures and redundant manipulators. We introduce then

Abstract—Mobile robots offer a typical example of systems with nonholonomic constraints. Several controllers have been proposed in the literature for stabilizing these systems. However, few experimental studies have been reported comparing the characteristics and the performance of these controllers with respect to neglected dynamics, quantization, noise, delays, etc. In this paper, we use a Khepera mobile robot to perform experimental comparison of several control laws. Khepera has two dc motor-powered wheels and introduces many realistic difficulties, such as different motor dynamics for the two wheels, time delay, quantization, sensor noise, and saturation. We emphasize the implementation difficulties of two discontinuous controllers proposed herein, and we compare their performance with several other controllers reported in the literature. Ways to improve the performance of each controller are also discussed. Index Terms—Experimental results, nonholonomic systems, stabilization, tracking, wheeled robots. I.