A guiding vector field algorithm for path following control of nonholonomic mobile robots

In this paper we propose an algorithm for path following control of the nonholonomic mobile robot based on the idea of the guiding vector field (GVF). The desired path may be an arbitrary smooth curve in its implicit form, that is, a level set of a predefined smooth function. Using this function and the robot’s kinematic model, we design a GVF, whose integral curves converge to the trajectory. A nonlinear motion controller is then proposed which steers the robot along such an integral curve, bringing it to the desired path. We establish global convergence conditions for our algorithm and demonstrate its applicability and performance by experiments with wheeled robots

Circular formation control of fixed-wing UAVs with constant speeds

In this paper we propose an algorithm for stabilizing circular formations of fixed-wing UAVs with constant speeds. The algorithm is based on the idea of tracking circles with different radii in order to control the inter-vehicle phases with respect to a target circumference. We prove that the desired equilibrium is exponentially stable and thanks to the guidance vector field that guides the vehicles, the algorithm can be extended to other closed trajectories. One of the main advantages of this approach is that the algorithm guarantees the confinement of the team in a specific area, even when communications or sensing among vehicles are lost. We show the effectiveness of the algorithm with an actual formation flight of three aircraft. The algorithm is ready to use for the general public in the open-source Paparazzi autopilot.Comment: 6 pages, submitted to IROS 201

Mobile Robot Path Following Controller Based On the Sirms Dynamically Connected Fuzzy Inference Model

This paper presents a simple and effective way to implement a path following controller for a differential drive wheeled mobile robot based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model. The control of the mobile robot is divided into two control actions performed in parallel; the heading and the velocity controller. For the heading controller, each input item is assigned with a SIRM and a dynamic importance degree (DID). The velocity controller structure was modified to simplify the design and to fulfill the requirements of the path following method. Here, a common DID is used. The SIRMs and the dynamic importance degrees are designed such that the angular velocity control takes the highest priority over the linear velocity control of the mobile robot. By using the SIRMs and the dynamic importance degrees, the priority orders of the controls are automatically adjusted according to navigation situations. The proposed fuzzy controller has a simple and intuitively understandable structure, and executes the two control actions entirely in parallel. Simulation results show that the proposed fuzzy controller can drive a mobile robot smoothly with a high precision through a series of waypoints to attain its final target in short time

Mobile Robot Path Following Controller Based On the Sirms Dynamically Connected Fuzzy Inference Model

This paper presents a simple and effective way to implement a path following controller for a differential drive wheeled mobile robot based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model. The control of the mobile robot is divided into two control actions performed in parallel; the heading and the velocity controller. For the heading controller, each input item is assigned with a SIRM and a dynamic importance degree (DID). The velocity controller structure was modified to simplify the design and to fulfill the requirements of the path following method. Here, a common DID is used. The SIRMs and the dynamic importance degrees are designed such that the angular velocity control takes the highest priority over the linear velocity control of the mobile robot. By using the SIRMs and the dynamic importance degrees, the priority orders of the controls are automatically adjusted according to navigation situations. The proposed fuzzy controller has a simple and intuitively understandable structure, and executes the two control actions entirely in parallel. Simulation results show that the proposed fuzzy controller can drive a mobile robot smoothly with a high precision through a series of waypoints to attain its final target in short time

The Isoline Tracking in Unknown Scalar Fields with Concentration Feedback

The isoline tracking of this work is concerned with the control design for a sensing vehicle to track a desired isoline of an unknown scalar field. To this end, we propose a simple PI-like controller for a Dubins vehicle in the GPS-denied environments. Our key idea lies in the design of a novel sliding surface based error in the standard PI controller. For the circular field, we show that the P-like controller can globally regulate the vehicle to the desired isoline with the steady-state error that can be arbitrarily reduced by increasing the P gain, and is eliminated by the PI-like controller. For any smoothing field, the P-like controller is able to achieve the local regulation. Then, it is extended to the cases of a single-integrator vehicle and a doubleintegrator vehicle, respectively. Finally, the effectiveness and advantages of our approaches are validated via simulations on the fixed-wing UAV and quadrotor simulators