In this paper, we look into the dynamic motion planning and control of an unmanned aerial vehicle, namely, the quadrotor, governed by its dynamical equations. It is shown for the first time that the Direct or the Second Method of Lyapunov is an effective tool to derive a set of continuous nonlinear control laws that not only provide smooth trajectories from a designated initial position to a designated target, but also continuously minimise the roll and pitch of the quadrotor en route to its targets. The latter successfully addresses the challenging problem of a quadrotor autonomously transporting valuable and fragile payloads safely to the designated target. Computer simulations are used to illustrate the effectiveness of the proposed control laws. INDEX TERMS Artificial potential field, Lyapunov-based control scheme, quadrotor, stability, UAV.

This paper addresses motion control of a cooperative intelligent transport system (C-ITS) of nonholonomic mobile robots navigating a dynamic environment while maintaining a locally rigid formation. We consider the design of acceleration-based control inputs that govern the motion of cooperative intelligent transport system (C-ITS) using the artificial potential fields method for the avoidance of obstacles and attraction to designated targets. The control scheme utilizes a new leader-follower strategy using Cartesian coordinates to accomplish a collision-free locally rigid formation of an autonomous and intelligent transportation system. The concepts of virtual parking bays and minimum distance technique (MDT) are utilized to attain prescribed orientations of the formation at the final destination. The robustness of the control scheme is established by considering the effect noise on the formation, while the effectiveness of the proposed nonlinear control laws is demonstrated through computer simulations.

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We develop a set of novel autonomous controllers for multiple point-mass robots or agents in the presence of wall-like rectangular planes in three-dimensional space. To the authors’ knowledge, this is the first time that such a set of controllers for the avoidance of rectangular planes has been derived from a single attractive and repulsive potential function that satisfies the conditions of the Direct Method of Lyapunov. The potential or Lyapunov function also proves the stability of the system of the first-order ordinary differential equations governing the motion of the multiple agents as they traverse the three-dimensional space from an initial position to a target that is the equilibrium point of the system. The avoidance of the walls is via an approach called the Minimum Distance Technique that enables a point-mass agent to avoid the wall from the shortest distance away at every unit time. Computer simulations of the proposed Lyapunov-based controllers for the multiple point-mass agents navigating in a common workspace are presented to illustrate the effectiveness of the controllers. Simulations include towers and walls of tunnels as obstacles. In the simulations, the point-mass agents also show typical swarming behaviors such as split-and-rejoin maneuvers when confronted with multiple tower-like structures. The successful illustration of the effectiveness of the controllers opens a fertile area of research in the development and implementation of such controllers for Unmanned Aerial Vehicles such as quadrotors.

SUMMARY This paper addresses the motion planning and control problem of a system of 1-trailer robots navigating a dynamic environment cluttered with obstacles including a swarm of boids. A set of nonlinear continuous control laws is proposed via the Lyapunov-based Control Scheme for collision, obstacle, and swarm avoidances. Additionally, a leader–follower strategy is utilized to allow the flock to split and rejoin when approaching obstacles. The effectiveness of the control laws is demonstrated through numerical simulations, which show the split and rejoin maneuvers by the flock when avoiding obstacles while the swarm exhibits emergent behaviors.