Hybrid control of a constrained velocity unicycle with local sensing

Abstract

Abstract-This paper introduces a hybrid control scheme for steering a non-holonomic agent with limited sensing capabilities and input constraints through a stationary but unknown workspace, occupied by arbitrarily shaped obstacles. The considered constraints (i.e. constant linear and bounded angular velocities) apply to a wide category of vehicle systems. Limited sensing is realized by a radially bounded sensing device. The proposed hybrid controller respects the kinematic constraints while guaranteeing obstacle avoidance and convergence to a specified goal configuration. In addition to the analytical guarantees, we demonstrate the effectiveness of the proposed hybrid control scheme through non-trivial computer simulations.

Hybrid Planning and Control for Multiple Fixed-Wing Aircraft under Input Constraints

“…ii The equilibrium of the system (2) is asymptotically stable if and only if (22) holds and there exists j such that V j (x(t j k ))) → 0 as k → ∞.…”

“…The paper 19 discusses how hierarchical structures can help with managing complexity, in the sense that they require less detailed models at higher levels (discrete abstraction). In the context of UAV planning and control, several hybrid or switched systems approaches have been developed; for instance, 20 presents a solution that yields convergence to an objective circular path, 21 presents a hybrid law for autonomous transition flight, and 22 proposes a safe hybrid control scheme for nonholonomic vehicles flying through an obstacle environment. There has been lot of work on conflict resolution of two aircraft system, see.…”

Robust consensus of unicycles using ternary and hybrid controllers

“…Smooth time‐varying control laws for a network of unicycles have been designed to study the feasibility of stabilizing the network over a directed graph , consensus of the speeds and headings , and consensus of only the positions of unicycles . Examples of hybrid controllers for unicycles include steering a single unicycle subject to input constraints and through obstacles and deployment of a group of unicycles using locational optimization .…”

Controlling the Relative Agent Motion in Multi-Agent Formation Stabilization

“…This development can lead to hybrid multi-agent systems that can reliably relay information within the network. An alternative way to ensure a desired rate of change of the network structure is to enforce hard bounds on the individual agent velocities [15]. However, this approach is overly conservative, as it will generally require from the agents to move slow, which hinders real time implementation of this algorithm.…”