Closed Loop Navigation for Mobile Agents In Dynamic Environments

Decision and Control, …, 2003

In this paper we present an extension to the navigation function methodology [6], [7] to the case where unmodelled obstacles are introduced in the workspace. A feedback control law is derived, based on the navigation function built on the initial workspace. Global convergence and collision avoidance properties are established. The derived closed form control law is suitable for real time implementation. Collision avoidance and global convergence properties are verified through computer simulations.

Robotics and Automation, …, 2002

Abstract|A nonholonomic motion planner for mobile manipulators moving in cluttered environments is presented. The approach is based on a discontinous feedback law under the infuence of a special potential eld. Convergence is shown via Lyapunov's direct method. Utilizing redundancy, the methodology allows the system to perform secondary, con guration dependent, objectives such as singularity avoidance. It introduces an e cient feedback scheme for real time navigation of nonholonomic systems.

Intelligent Robots and …, 2001

This paper presents a motion planner and nonholonomic controller for a mobile robot, with global collision avoidance and convergence properties. This closed loop approach combines appropriately designed (dipolar) potential fields with discontinuous feedback and is suitable for real time implementation. It makes use of a novel kind of Lyapunov functions which are useful for nonholonomic navigation. The obstacle avoidance and global asymptotic stability properties of the closed loop system are verified through computer simulations.

International Journal on Advanced Science, Engineering and Information Technology, 2016

In this paper, path planning which is based on Artificial Potential Field (APF) and the kinematic based control is integrated in order to solve an issue in the APF. Usually, the APF assumes the robot is modeled as a point mass. It means that the robot can move in any direction and neglect the nonholonomic constraint. In order to solve such a problem, the APF should be considered as part of the control system. This research proposed an approach integrating APF and control system under nonholonomic constraint. Naturally, the force of the APF can be used as linear velocity in the control system. Then, waypoint of APF is used as equilibrium point of kinematic control. In order to validate the proposed method, the experimental setup conducted on loop simulation. The scenario is that the robot moves along the certain trajectory to reach the goal point. The obstacle was set in between the robot and the goal point. The initial, goal, and the obstacles are set randomly. The experiments show that the integration of the proposed method can be implemented successfully. The real obstacle avoidance method and fulfilling the nonholonomic constraint are the proof that the method is running well. The results show that the integrated proposed method meets convergent and stable.

2012

This paper suggests a new way for nonholonomic mobile robots to navigate in obstacle environments using potential fields based on navigation functions. The proposed strategy is a time-invariant feedback control design with the distinguishing feature that it requires almost no switching compared to alternative methodologies of the same nature. Asymptotic convergence with collision avoidance for the proposed approach is established analytically, and the method is demonstrated on a differential-drive skid steering mobile robot.

Intelligent Robots and Systems' 91.' …, 1991

A b s t r a c t This paper presents a unified appnmch to the navigation and control of a mobile robot. In the past, path planning has often been referred to as a 'high level" task and has been completely sepamted from the so called 'lower level" control of a real mobile vehicle. We consider here the total energy of a mobile vehicle when influenced under a goal seeking navigation strategy. This energy function is used to produce a control law directly to drive a mobile vehicle. We also incorpomte directly an estimate of an artificial repulsive potential field into the low level controller.

Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), 2000

In this paper, a novel biologically inspired neural net,work approach is proposed for real-time collision-free path planning and tracking control of a nonholonomic mobile robot in a nonstationary environment. The real-time robot trajectory with obstacle avoidance is generated by a topologically organized neural network, where the dynamics of each neuron is characterized by a shunting equation. The varying environment is represented by the dynamic activity landscape of the neural network, where the neural activity propagation is subject to the kinematic constraint of the nonholonomic mobile robots. The real-time tracking velocities are generated by a novel neural dynamics based controller, which is based on two shunting models and the backstepping technique. Unlike the backstepping controllers that produce non-smooth velocity commands with sharp jumps, the proposed tracking controller is capable of generating smooth, continuous commands not suffering from velocity jumps. The effectiveness and efficiency of the proposed approach are demonstrated through simulation and comparison studies.

… and Automation, IEEE …, 2003

This paper presents the first motion planning methodology applicable to articulated, non-point nonholonomic robots with guaranteed collision avoidance and convergence properties. It is based on a new class of nonsmooth Lyapunov functions (DILFs) and a novel extension of the navigation function method to account for non-point articulated robots. The Dipolar Inverse Lyapunov Functions introduced are appropriate for nonholonomic control and offer superior performance characteristics compared to existing tools. The new potential field technique uses diffeomorphic transformations and exploits the resulting pointworld topology. The combined approach is applied to the problem of handling deformable material by multiple nonholonomic mobile manipulators in obstacle environment to yield a centralized coordinating control law. Simulation results verify asymptotic convergence of the robots, obstacle avoidance, boundedness of object deformations and singularity avoidance for the manipulators.

IEEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications, 1990

This paper deals with the problem of planning and controlling the motion of non holonomic veliicles in a dynamic world. The work prrscnkd here is part of a more important system which w a s described in a previous communication . The contribution of this paper is tworold: (1) we present a Lrajeclory planner whose purpose is to determine a smooth trajectory C wllicli is maneuver rree and collision free wi(h respect to the static obstacles of the world. C is made up of straight segments and of circular arcs connected so that C is of class CL and the circular transitions are determined by building and searching a particular domain called the "space of curvature centers".

Systems & Control Letters, 2020

In this paper, we propose an obstacle avoidance controller for a disk-shaped holonomic robot with double-integrator dynamics and local sensing. The control objective is for the robot to converge to a target velocity while avoiding collisions with strictly convex obstacles in an unbounded environment. We assume that the robot has no information about the location and geometry of the obstacles, has no localization capabilities, and can only measure its own velocity and its relative position vector to the closest point on any obstacles in its sensing range. We first propose a potential-based controller for the case with a single obstacle, and we prove that the robot safely navigates past the obstacle and attains the desired velocity. For the case with multiple obstacles, we propose a switching control scheme in which the robot applies the single-obstacle controller for the closest obstacle at each instant. We investigate the correctness of this switching control law and demonstrate the absence of local stable equilibrium points that would trap the robot. We validate our analytical results through simulations of a robot that uses the proposed controllers to successfully navigate through an environment with strictly convex obstacles of various shapes and sizes.