2,443 research outputs found
Syntactic Complexity of Circular Semi-Flower Automata
We investigate the syntactic complexity of certain types of finitely
generated submonoids of a free monoid. In fact, we consider those submonoids
which are accepted by circular semi-flower automata (CSFA). Here, we show that
the syntactic complexity of CSFA with at most one `branch point going in' (bpi)
is linear. Further, we prove that the syntactic complexity of -state CSFA
with two bpis over a binary alphabet is
COCrIP: Compliant OmniCrawler In-pipeline Robot
This paper presents a modular in-pipeline climbing robot with a novel
compliant foldable OmniCrawler mechanism. The circular cross-section of the
OmniCrawler module enables a holonomic motion to facilitate the alignment of
the robot in the direction of bends. Additionally, the crawler mechanism
provides a fair amount of traction, even on slippery surfaces. These advantages
of crawler modules have been further supplemented by incorporating active
compliance in the module itself which helps to negotiate sharp bends in small
diameter pipes. The robot has a series of 3 such compliant foldable modules
interconnected by the links via passive joints. For the desirable pipe diameter
and curvature of the bends, the spring stiffness value for each passive joint
is determined by formulating a constrained optimization problem using the
quasi-static model of the robot. Moreover, a minimum friction coefficient value
between the module-pipe surface which can be vertically climbed by the robot
without slipping is estimated. The numerical simulation results have further
been validated by experiments on real robot prototype
Design and optimal springs stiffness estimation of a Modular OmniCrawler in-pipe climbing Robot
This paper discusses the design of a novel compliant in-pipe climbing modular
robot for small diameter pipes. The robot consists of a kinematic chain of 3
OmniCrawler modules with a link connected in between 2 adjacent modules via
compliant joints. While the tank-like crawler mechanism provides good traction
on low friction surfaces, its circular cross-section makes it holonomic. The
holonomic motion assists it to re-align in a direction to avoid obstacles
during motion as well as overcome turns with a minimal energy posture.
Additionally, the modularity enables it to negotiate T-junction without motion
singularity. The compliance is realized using 4 torsion springs incorporated in
joints joining 3 modules with 2 links. For a desirable pipe diameter (\text{\O}
75mm), the springs' stiffness values are obtained by formulating a constraint
optimization problem which has been simulated in ADAMS MSC and further
validated on a real robot prototype. In order to negotiate smooth vertical
bends and friction coefficient variations in pipes, the design was later
modified by replacing springs with series elastic actuators (SEA) at 2 of the 4
joints.Comment: arXiv admin note: text overlap with arXiv:1704.0681
Model Predictive Control for Autonomous Driving Based on Time Scaled Collision Cone
In this paper, we present a Model Predictive Control (MPC) framework based on
path velocity decomposition paradigm for autonomous driving. The optimization
underlying the MPC has a two layer structure wherein first, an appropriate path
is computed for the vehicle followed by the computation of optimal forward
velocity along it. The very nature of the proposed path velocity decomposition
allows for seamless compatibility between the two layers of the optimization. A
key feature of the proposed work is that it offloads most of the responsibility
of collision avoidance to velocity optimization layer for which computationally
efficient formulations can be derived. In particular, we extend our previously
developed concept of time scaled collision cone (TSCC) constraints and
formulate the forward velocity optimization layer as a convex quadratic
programming problem. We perform validation on autonomous driving scenarios
wherein proposed MPC repeatedly solves both the optimization layers in receding
horizon manner to compute lane change, overtaking and merging maneuvers among
multiple dynamic obstacles.Comment: 6 page
Numerics of High Performance Computers and Benchmark Evaluation of Distributed Memory Computers
The internal representation of numerical data, their speed of manipulation to generate the desired result through efficient utilisation of central processing unit, memory, and communication links are essential steps of all high performance scientific computations. Machine parameters, in particular, reveal accuracy and error bounds of computation, required for performance tuning of codes. This paper reports diagnosis of machine parameters, measurement of computing power of several workstations, serial and parallel computers, and a component-wise test procedure for distributed memory computers. Hierarchical memory structure is illustrated by block copying and unrolling techniques. Locality of reference for cache reuse of data is amply demonstrated by fast Fourier transform codes. Cache and register-blocking technique results in their optimum utilisation with consequent gain in throughput during vector-matrix operations. Implementation of these memory management techniques reduces cache inefficiency loss, which is known to be proportional to the number of processors. Of the two Linux clusters-ANUP16, HPC22 and HPC64, it has been found from the measurement of intrinsic parameters and from application benchmark of multi-block Euler code test run that ANUP16 is suitable for problems that exhibit fine-grained parallelism. The delivered performance of ANUP16 is of immense utility for developing high-end PC clusters like HPC64 and customised parallel computers with added advantage of speed and high degree of parallelism
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