A program executing on a low-end embedded system, such as a smart-card, faces scarce memory resources and fixed execution time constraints. We demonstrate that factorization of common instruction sequences in Java bytecode allows the memory footprint to be reduced, on average, to 85% of its original size, with a minimal execution time penalty. While preserving Java compatibility, our solution requires only a few modifications which are straightforward to implement in any JVM used in a low-end embedded system.

Drones are becoming increasingly valuable tools in wildlife studies due to their ability to access remote areas and offer high-resolution information with minimal human interference. Their application is, however, causing concern regarding wildlife disturbance. This review synthesizes the existing literature on how animals within terrestrial, aerial, and aquatic environments are impacted by drone disturbance in relation to operational variables, sensory stimulation, species-specific sensitivity, and physiological and behavioral responses. We found that drone altitude, speed, approach distance, and noise levels significantly influence wildlife responses, with some species exhibiting increased vigilance, flight responses, or physiological stress. Environmental context and visual cues are also involved in species detection of drones and disturbance thresholds. Although the short-term response to behavior change has been well documented, long-term consequences of repeated drone exposure remain poorly known. This paper identifies the necessity for continued research into drone–wildlife interactions, with an emphasis on the requirement to minimize disturbance by means of improved flight parameters and technology.

SUMMARY: Programming robotic assembly for industrial small-batch production is challenging; hence, it is vital to increase robustness and reduce development effort in order to achieve flexible robotic automation. A human who has made an assembly error will often simply undo the process until the error is undone and then restart the assembly. Conceptually, robots could do the same. This paper introduces a programming model that enables robot assembly programs to be executed in reverse. We investigate the challenges in running robot programs backwards and present a classification of reversibility characteristics. We demonstrate how temporarily switching the direction of program execution can be an efficient error recovery mechanism. Moreover, we demonstrate additional benefits arising from supporting reversibility in an assembly language, such as increased code reuse and automatically derived disassembly sequences. As a default approach to reversibility, we use program inversion and statement-level inversion of commands, but with a novel override option providing alternative sequences for asymmetric reverse actions. To efficiently program for this model, this paper introduces a new domain-specific language, SCP-RASQ (Simple C++ Reversible Assembly SeQuences). In initial experiments, where 200 consecutive assemblies of two industrial cases were performed, 18 of 22 errors were corrected automatically using only the trial-and-error capabilities that come from reverse execution.

Robotic assembly tasks are in general difficult to program and require a high degree of precision. As the complexity of the task increases it becomes increasingly unlikely that tasks can always be executed without errors. Preventing errors beyond a certain point is economically infeasible, in particular for small-batch productions. As an alternative, we propose a system for automatically handling certain classes of errors instead of preventing them. Specifically, we show that many operations can be automatically reversed. Errors can be handled through automatic reverse execution of the control program to a safe point, from which forward execution can be resumed. This paper describes the principles behind automatic reversal of robotic assembly operations, and experimentally demonstrates the use of a domain-specific language that supports automatic error handling through reverse execution. Our contribution represents the first experimental demonstration of reversible computing principles applied to industrial robotics.