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This distributed control architecture includes vision processing, navigation and on-line walking pattern generation algorithm.
This study mainly shows the efficiencies of the proposed pattern generation algorithm and trajectory generation algorithm for the brick-laying task.
So in order to simplify the process of gait generation and extend several typical gaits into arbitrary gaits during turning of a bio-inspired hexapod robot, taking insect gait as inspiration, an arbitrary gait pattern generation algorithm is proposed.
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A detailed description of different pattern generation algorithms along with the complexity is presented in [ 18- 21].
This study proposes an online walking-pattern generation algorithm with footstep adjustment.
For its practical implementation, this paper introduces two algorithms: pattern generation (PG) algorithm and pattern identification (PI) algorithm.
Very recently, Paul and Murshed [16] proposed a content-based pattern generation (CPG) algorithm to generate eight patterns from the given moving regions.
In this paper, we propose a near-optimal content-based pattern generation (OCPG) algorithm which outperforms the existing approach.
In this paper, we present an extensible Max-SAT based automatic test pattern generation (ATPG) algorithm for cancer therapy.
Lin and Khatri [ 2] considers the aberrant behavior of signaling pathways during cancer as faults in an electronic circuit and presents a Max-SAT based automatic test pattern generation (ATPG) algorithm for cancer therapy.
Using this stuck-at fault model, automatic test pattern generation (ATPG) algorithms determine a set of tests (bit vectors on the inputs of the circuit) to test for stuck-at faults in the circuit.
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