Technical Reportshttps://udspace.udel.edu/handle/19716/49502024-05-25T07:43:00Z2024-05-25T07:43:00Z61Behavior modeling for hybrid robotic vehiclesRawal, Chetanhttps://udspace.udel.edu/handle/19716/103812022-11-30T19:47:40Z2011-10-01T00:00:00Zdc.title: Behavior modeling for hybrid robotic vehicles
dc.contributor.author: Rawal, Chetan
dc.description.abstract: The behavior of a certain class of hybrid robotic systems can be expressed
using formal languages. In this work, we show how languages can be generated from
discrete abstractions of such hybrid systems; that these languages are regular; and
they belong to the star free (SF) class of the Sub-regular hierarchy.
Planning and control of hybrid systems is typically difficult due to the computational
cost involved in predicting the system’s future states, since the states can
take infinite values while evolving along the trajectories of continuous dynamics. A
discrete abstraction of the hybrid system can reduce these values to a finite number,
thereby fascilitating the solution to the reachability problem. Abstraction enables
us to focus on planning the system’s overall behavior through controller sequences
observed in the abstract system, instead of dealing with the dynamics associated
with each controller.
2011-10-01T00:00:00ZTopology Optimization in Cellular Neural NetworksBhambhani, VarshaTanner, Herberthttps://udspace.udel.edu/handle/19716/56582022-11-30T19:47:40Z2010-07-01T00:00:00Zdc.title: Topology Optimization in Cellular Neural Networks
dc.contributor.author: Bhambhani, Varsha; Tanner, Herbert
dc.description.abstract: This paper establishes a new constrained combinatorial optimization approach to the design of cellular neural
networks with sparse connectivity. This strategy is applicable to cases where maintaining links between neurons
incurs a cost, which could possibly vary between these links. The cellular neural network’s interconnection topology
is diluted without significantly degrading its performance, the network quantified by the average recall probability
for the desired patterns engraved into its associative memory. The dilution process selectively removes the links that
contribute the least to a metric related to the size of system’s desired memory pattern attraction regions. The metric
used here is the magnitude of the network’s nodes’ stability parameters, which have been proposed as a measure for
the quality of memorization. Further, the efficiency of the method is justified by comparing it with an alternative
dilution approach based on probability theory and randomized algorithms. We demonstrate by means of an example
that this method of network dilution based on combinatorial optimization produces cheaper associative memories that
in general trade off performance for cost, and in many cases the performance of the diluted network is on par with
the original system. Also the randomized algorithm based method results in same network performance in terms of
network recall probability.
2010-07-01T00:00:00ZMulti-agent navigation functions: Have we missed something?Tanner, HerbertBoddu, Adithyahttps://udspace.udel.edu/handle/19716/56572022-11-30T19:47:40Z2010-08-01T00:00:00Zdc.title: Multi-agent navigation functions: Have we missed something?
dc.contributor.author: Tanner, Herbert; Boddu, Adithya
dc.description.abstract: This paper presents a methodology for designing (centralized) control laws which can probably steer a group of
robotic agents to fall into a formation of arbitrary shape, while following collision free trajectories. The scheme is
based on the concept of navigation functions, a special type of artificial potential functions without local minima,
and the paper describes how this idea can be generalized from its original formulation for single-robot systems,
to multi-robot formations. We indicate why existing solutions that have appeared in literature, although potentially
functional, may not have been accompanied with sufficient guarantees against the possibility of the system ever getting
stuck in non-optimal configurations. The problem is therefore revisited here under a new set of assumptions, a new
construction is proposed, and the properties of this new centralized potential function are analytically demonstrated.
2010-08-01T00:00:00ZComposition of Context-Free Motion Description LanguagesZhang, WenqiTanner, Herberthttps://udspace.udel.edu/handle/19716/56562022-11-30T19:47:40Z2010-01-01T00:00:00Zdc.title: Composition of Context-Free Motion Description Languages
dc.contributor.author: Zhang, Wenqi; Tanner, Herbert
dc.description.abstract: We introduce a new formalism to define compositions of interacting heterogeneous systems, described by extended
motion description languages (MDLes). The novelty of the formalism is in producing a composed system with
a behavior that could be a superset of the union of the behaviors of its generators. We prove closedness of MDLes
under this composition and we indicate that in the class of systems modeled using MDLes, language equivalence is
decidable. Our approach consists of representing MDLes as normed processes, recursively defined as a guarded system
of recursion equations in restricted Greibach Normal Form over a basic process algebra. Basic processes have
well defined semantics for composition, which we exploit to establish the properties of our composed MDLes.
2010-01-01T00:00:00ZRandomized Model Predictive NavigationTanner, HerbertPiovesan, Jorgehttps://udspace.udel.edu/handle/19716/49522022-11-30T19:47:40Z2010-02-01T00:00:00Zdc.title: Randomized Model Predictive Navigation
dc.contributor.author: Tanner, Herbert; Piovesan, Jorge
dc.description.abstract: A new methodology for implementing nonlinear receding horizon optimization is presented, with direct application
to robot navigation in cluttered environments. The methodology combines elements from statistical learning
theory with nonlinear receding horizon schemes that use control Lyapunov functions as terminal costs, while relaxing
the conditions on the time derivatives of the latter, based on a new result for stability of nonlinear systems with
switching dynamics. As the theoretical analysis indicates, and numerical results verify, the proposed receding horizon
scheme can utilize terminal costs that are not control Lyapunov functions. The resulting strategy is shown to
outperform traditional potential field-based techniques, even when additional optimization objectives are imposed,
and allows for trade-offs between performance and computational complexity.
2010-02-01T00:00:00ZModeling of a Hexapod Robot; Kinematic Equivalence to a UnicyclePanagou, DimitraTanner, Herberthttps://udspace.udel.edu/handle/19716/49512022-11-30T19:47:40Z2009-04-01T00:00:00Zdc.title: Modeling of a Hexapod Robot; Kinematic Equivalence to a Unicycle
dc.contributor.author: Panagou, Dimitra; Tanner, Herbert
dc.description.abstract: This report describes the kinematic and dynamic modeling of a hexapod robot. The 6-DOF (degrees of freedom)
analytical kinematic and dynamic equations of motion are derived following the classical Newtonian mechanics.
Under certain task-specific assumption, it is shown that the complex 6-DOF model can be simplified, resulting in an
abstract model. Specifically, the motion of the robot on the horizontal plane in particular is described by the unicycle
model with dynamic extension. The abstract unicycle model exhibits restricted behavior compared to the concrete
hexapod model, but facilitates motion planning and control design and ensures that higher level control plans are
implementable as low level control laws.
2009-04-01T00:00:00Z