4,593 research outputs found
Formation of Multiple Groups of Mobile Robots Using Sliding Mode Control
Formation control of multiple groups of agents finds application in large
area navigation by generating different geometric patterns and shapes, and also
in carrying large objects. In this paper, Centroid Based Transformation (CBT)
\cite{c39}, has been applied to decompose the combined dynamics of wheeled
mobile robots (WMRs) into three subsystems: intra and inter group shape
dynamics, and the dynamics of the centroid. Separate controllers have been
designed for each subsystem. The gains of the controllers are such chosen that
the overall system becomes singularly perturbed system. Then sliding mode
controllers are designed on the singularly perturbed system to drive the
subsystems on sliding surfaces in finite time. Negative gradient of a potential
based function has been added to the sliding surface to ensure collision
avoidance among the robots in finite time. The efficacy of the proposed
controller is established through simulation results.Comment: 8 pages, 5 figure
New Shop Floor Control Approaches for Virtual Enterprises
The virtual enterprise paradigm seems a fit response to face market instability and the volatile nature of business opportunities increasing enterprise’s interest in similar forms of networked organisations. The dynamic environment of a virtual enterprise requires that partners in the consortium own reconfigurable shop floors. This paper presents new approaches to shop floor control that meet the requirements of the new industrial paradigms and argues on work re-organization at shop floor level.virtual enterprise; networked organisations
Enabling flexibility through strategic management of complex engineering systems
”Flexibility is a highly desired attribute of many systems operating in changing or uncertain conditions. It is a common theme in complex systems to identify where flexibility is generated within a system and how to model the processes needed to maintain and sustain flexibility. The key research question that is addressed is: how do we create a new definition of workforce flexibility within a human-technology-artificial intelligence environment?
Workforce flexibility is the management of organizational labor capacities and capabilities in operational environments using a broad and diffuse set of tools and approaches to mitigate system imbalances caused by uncertainties or changes. We establish a baseline reference for managers to use in choosing flexibility methods for specific applications and we determine the scope and effectiveness of these traditional flexibility methods.
The unique contributions of this research are: a) a new definition of workforce flexibility for a human-technology work environment versus traditional definitions; b) using a system of systems (SoS) approach to create and sustain that flexibility; and c) applying a coordinating strategy for optimal workforce flexibility within the human- technology framework. This dissertation research fills the gap of how we can model flexibility using SoS engineering to show where flexibility emerges and what strategies a manager can use to manage flexibility within this technology construct”--Abstract, page iii
Hierarchical generative modelling for autonomous robots
Humans can produce complex whole-body motions when interacting with their
surroundings, by planning, executing and combining individual limb movements.
We investigated this fundamental aspect of motor control in the setting of
autonomous robotic operations. We approach this problem by hierarchical
generative modelling equipped with multi-level planning-for autonomous task
completion-that mimics the deep temporal architecture of human motor control.
Here, temporal depth refers to the nested time scales at which successive
levels of a forward or generative model unfold, for example, delivering an
object requires a global plan to contextualise the fast coordination of
multiple local movements of limbs. This separation of temporal scales also
motivates robotics and control. Specifically, to achieve versatile sensorimotor
control, it is advantageous to hierarchically structure the planning and
low-level motor control of individual limbs. We use numerical and physical
simulation to conduct experiments and to establish the efficacy of this
formulation. Using a hierarchical generative model, we show how a humanoid
robot can autonomously complete a complex task that necessitates a holistic use
of locomotion, manipulation, and grasping. Specifically, we demonstrate the
ability of a humanoid robot that can retrieve and transport a box, open and
walk through a door to reach the destination, approach and kick a football,
while showing robust performance in presence of body damage and ground
irregularities. Our findings demonstrated the effectiveness of using
human-inspired motor control algorithms, and our method provides a viable
hierarchical architecture for the autonomous completion of challenging
goal-directed tasks
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