Architecture of Computing Systems (Lecture Notes in Computer ...

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68 B. Jakimovski, B. Meyer, and E. Maehle demonstrator OSCAR - Fig. 2 (a). The results from experiments are represented in Fig. 6 (a, b, c). In figures Fig. 6 (a), (b), (c), the x-axis represents the time in seconds and the y-axis represents the swing / stance phases by the robot’s legs. )SW-swing phase; ST-stance phase.) Normally we perform our experiments on our hexapod robot using emergent gait patterns generated in a distributed manner by each of the robot’s legs mapped suitably into the ORCA architecture. However, in these experiments we have chosen to use the insect-inspired tripod gait walking pattern [35] [36] (which can be simulated with centralized robot control) just to better represent the results of our experiments done on self-synchronization. In this case swing/stance phases by robot’s legs can be easily distinguished on the figure resulting from experiments, in contrast to emergent type of walking where the gait pattern often changes and therefore might obscure the idea of this research. Another factor that has been brought in the experiments is that the start of the synchronization is not done by some external influence, but this start has been pre-programmed so the experiments can be focused on principle of the synchronization process itself. The experiments were defined as following: Fig.6 (a): The first experiment is about self-synchronization by prolongation of the robot’s swing and stance phases. The robot starts to walk with a parameter length of 1 for the swing and stance phases. At first this parameter gets changed by the leg number 3 at time 23s during its stance phase. Then in the next cycle the neighboring legs 2 and 4 in the stance phase prolong their length parameters during their stance phases at time 28s. After this, at time 33s, the legs numbered 1 and 5 also synchronize their swing and stance length units to 2 in their stance phases. At time 38s also the leg numbered 0 synchronizes its length of swing and stance to 2 length units. In a similar fashion the self-synchronization and prolongation of stance and swing phases is further done for each of the legs prolonging from 2 length units to 3 length units. At the end a gait pattern gets self-synchronized with length units 3 for the swing and stance phases. Fig.6 (b): In the second experiment a shortening of the gait pattern takes place from 5 length units to 3 length units over the course of the experiment. The robot starts to walk with length parameter of 5 for swing and stance phases. At first at a time 17s the leg number 2 decreases its swing phase the swing / stance parameter from 5 length units to 4 length units. After that, in the second cycle the legs numbered 1 and 3 at time 22s in their swing phases decrease their stance / swing parameters to length of 4 units. Then follows the synchronization by legs numbered 0 and 4 at time 27s in their swing phases and they synchronize their length parameters to length of 4 units. At time 32s also leg number 5 synchronizes its stance / swing length parameter to length of 4. In similar fashion the self-synchronization also continues for stance / swing lengths up to 87s of time when all the legs have the length of the stance / swing parameter of 3. Fig.6 (c): In this experiment we have performed dynamic self-synchronization of the robot walking gait pattern starting from stance / swing parameter length of 1 then increasing to parameter length of 3 and then decreasing again to stance / swing parameter length of 1. The first change of the parameter occurs by the leg number 5
Firefly Flashing Synchronization as Inspiration for Self-synchronization 69 (a) (b) (c) Fig. 6. (a) Self-synchronization by prolongation of the robot’s swing and stance phases; (b) Self-synchronization by shortening of the robot’s swing and stance phases; (c) Selfsynchronization by prolongation and shortening of the robot’s swing and stance phases
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Lecture Notes in Computer Science 5
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Volume Editors Christian Müller-Sc
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General Chair Organization Christia
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Organization IX Hartmut Schmeck Kar
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Keynote Table of Contents HyVM - Hy
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Table of Contents XIII JetBench:AnO
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How to Enhance a Superscalar Proces
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4 J. Mische et al. The Real-time Vi
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6 J. Mische et al. 4.1 Instruction
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8 J. Mische et al. Additionally the
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10 J. Mische et al. % of unused pip
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16 G. Aşılıoğlu, E.M. Kaya, and
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122 P. Petoumenos et al. As long as
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124 P. Petoumenos et al. comparable
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Exploiting Inactive Rename Slots fo
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128 M. Kayaalp et al. In a supersca
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130 M. Kayaalp et al. INSTRUCTION 1
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132 M. Kayaalp et al. time. Alterna
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134 M. Kayaalp et al. Fig. 3. Numbe
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136 M. Kayaalp et al. The results o
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Efficient Transaction Nesting in Ha
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140 Y. Liu et al. HTMs include TCC
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142 Y. Liu et al. rollback T0 begin
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144 Y. Liu et al. Processor core Pr
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146 Y. Liu et al. 5.2 Results and A
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148 Y. Liu et al. decreases, partia
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Decentralized Energy-Management to
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152 B. Becker et al. Furthermore, t
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154 B. Becker et al. An optimizing
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156 B. Becker et al. smart-home man
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158 B. Becker et al. freedom like w
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160 B. Becker et al. Power [W] 4500
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EnergySaving Cluster Roll: Power Sa
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166 M.F. Dolz et al. This daemon al
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168 M.F. Dolz et al. been submitted
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170 M.F. Dolz et al. On the other h
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172 M.F. Dolz et al. at the inactiv
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Effect of the Degree of Neighborhoo
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176 T. Abdullah et al. A zone based
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178 T. Abdullah et al. A consumer/p
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180 T. Abdullah et al. Messages 140
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184 T. Abdullah et al. % Matchmakin
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A Tightly Coupled Accelerator Infra
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224 F. Nowak and R. Buchty where A
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226 F. Nowak and R. Buchty Fig. 3.
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228 F. Nowak and R. Buchty Table 2.
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230 F. Nowak and R. Buchty Table 4.
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Optimizing Stencil Application on M
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236 F. Xudong et al. compared to th
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242 F. Xudong et al. Speedup 14 12
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244 F. Xudong et al. 5 Related Work
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Abdullah, Tariq 174 Alima, Luc Onan
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