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We demonstrate how simple local sensing and control rules achieve usefil emergent behaviors in modular self-reconfigurable (metamorphic) robots. Our biologically inspired approach grows structures with the desired functionality even though the final shapes have some unspecified, random variation. By contrast, other self-reconfiguration algorithms require an a-priori exact descriptaon of a target shape for the given task, which may be dificult when a robot operates in uncertain environments. We present and evaluate several control algorithms through simulation experiments of Proteo, a metamorphic robot system.

We demonstrate how multiagent systems provide useful control techniques for modular self-reconfigurable (metamorphic) robots. Such robots consist of many modules that can move relative to each other, thereby changing the overall shape of the robot to suit different tasks. Multiagent control is particularly wellsuited for tasks involving uncertain and changing environments. We illustrate this approach through simulation experiments of Proteo, a metamorphic robot system currently under development.

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Address Space Layout Randomization (ASLR) is a defensive technique supported by many desktop and server operating systems. While smartphone vendors wish to make it available on their platforms, there are technical challenges in implementing ASLR on these devices. Pre-linking, limited processing power and restrictive update processes make it difficult to use existing ASLR implementation strategies even on the latest generation of smartphones. In this paper we introduce retouching, a mechanism for executable ASLR that requires no kernel modifications and is suitable for mobile devices. We have implemented ASLR for the Android operating system and evaluated its effectiveness and performance. In addition, we introduce crash stack analysis, a technique that uses crash reports locally on the device, or in aggregate in the cloud to reliably detect attempts to brute-force ASLR protection. We expect that retouching and crash stack analysis will become standard techniques in mobile ASLR implementations.