Ahmad A. Masoud

Constrained motion control using vector potential fields

Discusses the generation of a control signal that would instruct the actuators of a robotics manipulator to drive motion along a safe and well-behaved path to a desired target. The proposed concept of navigation control along with the tools necessary for its construction achieve this goal. The most significant tool is the artificial vector potential field which shows a better ability to steer motion than does a scalar potential field. The synthesis procedure emphasizes flexibility so that the effort needed to modify the control is commensurate with the change in the geometry of the workspace. Theoretical development along with simulation results are provided.

Decentralized Self-Organizing Potential Field-Based Control for Individually Motivated Mobile Agents in a Cluttered Environment: A Vector-Harmonic Potential Field Approach

Spatial multiagency has been receiving growing attention from researchers exploring many of the aspects and modalities of this phenomenon. The aim is to develop the theoretical background needed for a multitude of applications involving the sharing of resources by more than one agent. A traffic management system is one of these applications. Here, a large group of mobile robots that are operating in communication-limited, and sensory-limited modes are required to cope with each others presence as well as the contents of their environment while preserving their ability to reach their preset independent goals. This paper explores the construction of a decentralized traffic controller for a large group of agents sharing a workspace with stationary forbidden regions. The suggested multiagent motion controller is complete provided that a lenient condition on the geometry of the workspace is upheld. It has a low computational effort that linearly increases with the number of agents. The controller is also self-organizing; therefore, it is able to deal, on its own, with incomplete information and unexpected situations. In addition to the above, the controller has an open structure to enable any agent to join or leave the group without the remaining agents having to adjust the manner in which they function. To meet these requirements, a definition of decentralization is suggested. This definition equates decentralization to self-organization in a group of agents operating in an artificial-life mode. The definition is used to provide guidelines for the construction of the multiagent controller. The controller is realized using the potential field approach. Theoretical developments, as well as simulation results, are provided

Robot navigation using a pressure generated mechanical stress field: "the biharmonic potential approach"

This paper suggests a new approach for navigation in a known environment. The approach is based on the biharmonic potential fields which govern mechanical stress fields in homogeneous solids. It is observed that a path generated by such a technique is free of sharp turns that may appear in its counterpart that is generated from an underlying harmonic potential. This in turns makes a path from the former more dynamically suitable for traversal. Also, the navigation field is extracted from the biharmonic potential in a manner that bypass the rapidly vanishing field problem which is encountered in the harmonic potential approach. Development of the biharmonic approach, simulation results, as well as comparison with the Neumann and Dirichlet setting of the harmonic approach are provided.<<ETX>>

Kinodynamic Motion Planning

This article extends the capabilities of the harmonic potential field (HPF) approach to planning to cover both the kinematic and dynamic aspects of a robots motion. The suggested approach converts the gradient guidance field from a harmonic potential to a control signal by augmenting it with a novel type of damping forces called nonlinear, anisotropic, damping forces (NADF). The HPF (harmonic potential field) approach to planning is emerging as a powerful paradigm for the guidance of autonomous agents.

A Delay-Tolerant Potential-Field-Based Network Implementation of an Integrated Navigation System

Network controllers (NCs) are devices that are capable of converting dynamic, spatially extended, and functionally specialized modules into a taskable goal-oriented group called networked control system. This paper examines the practical aspects of designing and building an NC that uses the Internet as a communication medium. It focuses on finding compatible controller components that can be integrated via a host structure in a manner that makes it possible to network, in real-time, a webcam, an unmanned ground vehicle (UGV), and a remote computer server along with the necessary operator software interface. The aim is to deskill the UGV navigation process and yet maintain a robust performance. The structure of the suggested controller, its components, and the manner in which they are interfaced are described. Thorough experimental results along with performance assessment and comparisons to a previously implemented NC are provided.

Managing the Dynamics of a Harmonic Potential Field-Guided Robot in a Cluttered Environment

This paper demonstrates the ability of the harmonic potential field (HPF) planning method to generate a well-behaved constrained path for a robot with second order dynamics in a cluttered environment. It is shown that HPF-based controllers may be developed for holonomic, as well as nonholonomic, robots to effectively suppress the effect of inertial forces on the robots trajectory while maintaining all the attractive features of a purely kinematic HPF planner. The capabilities of the suggested navigation controller are demonstrated using simulation results for the holonomic and nonholonomic cases.

Evolutionary action maps for navigating a robot in an unknown, multidimensional, stationary environment. II. Implementation and results

Here, the BGM that is suggested in the first part of this paper used to construct a complete path planner for an agent of arbitrary shape that is operating in a totally unknown, multidimensional, stationary environment. The planner does not require any a priori knowledge about the environment to guarantee that a path to the target will be found. Any a priori information about the environment, regardless of its degree of fragmentation or sparsity, can be integrated into the planning process to accelerate convergence and enhance the quality of the path. Details for constructing the planner along with experiments to demonstrate its capabilities are supplied.

Using hybrid vector-harmonic potential fields for multi-robot, multi-target navigation in a stationary environment

In this work, hybrid vector-harmonic potential fields are suggested for building a path planner for multirobot, multitarget navigation in a stationary environment. The suggested method is complete provided that the workspace satisfies a lenient geometrical condition. The operation of the planner is based on the bottom-up approach to behavior synthesis (instead of the common top-down approach). Such an approach proves effective in limiting the complexity of planning. The approach also enjoys significant flexibility, enabling the addition or removal of any number of robots from the workspace without having to adjust the manner in which the rest of the robots behave. Theoretical development, proofs, as well as simulation results are provided for a number of different robot workspace configurations.

Robot navigation using the vector potential approach

The artificial vector potential is used to construct a navigation control that can drive a manipulator to a target set while avoiding undesired regions in the workspace. It is shown that a vector potential field can better navigate a robot than a scalar potential field. The strategy that is suggested for constructing the navigation control is very flexible in the sense that it allows the addition or deletion of obstacles with minimal adjustment to the control. An efficient technique for generating the navigation field in the N-D space is proposed. Simulation results are provided.<<ETX>>

An informationally-open, organizationally-closed control structure for navigating a robot in an unknown, stationary environment

This paper examines the roots of purposive behavior in an agent surrounded by a stationary unknown environment. The investigation focuses on deriving a structure for a behavior generation mechanism (BGM) that would semantically embed an agent in the context of its environment. The BGM is made to adhere to the situated, embodied, intelligent, and emergent requirements that were suggested by Brooks for the construction of intelligent control architectures. Concepts from epistemology, artificial life, hybrid systems, and the potential field approach to planning are used. The suggested BGM utilizes both experience and synergy as drivers of action selection. The BGM is intended for use in the specific case of motion planning for a multidimensional agent of arbitrary shape operating in a multidimensional, unknown environment.