Representational Redundancy Research Articles

Reduction of LiDAR Point Cloud Maps for Localization of Resource-Constrained Robotic Systems

This article presents a method for mobile robotic systems to reduce the size of 3-D point cloud maps while achieving small localization errors even though the reduced maps are used for localization. Localization with dense depth maps especially in large environments could be computationally expensive, so not affordable for robotic systems with limited computational resources. Since such point cloud data collected using a multichannel 3-D LiDAR have representational redundancy, some amount of the data could be removed for compactness. However, existing methods demand annotations and descriptors defined by human experts or lose important spatial features for accurate localization. We propose a fully-automatic reduction method for reliable navigation of mobile systems with low computing power and limited storage. Given a full 3-D point cloud map, our method generates a graph whose vertices and edges represent robot poses and the similarity between the data collected from a pair of robot poses, respectively. Each robot pose is associated with a point cloud set. We find a dominating set of the graph, which is a subset of robot poses such that the robot can localize reliably only with the point clouds collected from those poses. Experimental results with indoor environments show that our system reduces the amount of map data up to 93% while not exceeding acceptable ranges of average translation and rotation errors, which are 0.25 m and 0.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> , respectively.

Non-power positional number representation systems, bijective numeration, and the Mesoamerican discovery of zero

Pre-Columbian Mesoamerica was a fertile crescent for the development of number systems. A form of vigesimal system seems to have been present from the first Olmec civilization onwards, to which succeeding peoples made contributions. We discuss the Maya use of the representational redundancy present in their Long Count calendar, a non-power positional number representation system with multipliers 1, 20, 18 × 20, …, 18 × 20n. We demonstrate that the Mesoamericans did not need to invent positional notation and discover zero at the same time because they were not afraid of using a number system in which the same number can be written in different ways. A Long Count number system with digits from 0 to 20 is seen later to pass to one using digits 0 to 19, which leads us to propose that even earlier there may have been an initial zeroless bijective numeration system whose digits ran from 1 to 20. Mesoamerica was able to make this conceptual leap to the concept of a cardinal zero to perform arithmetic owing to a familiarity with multiple and redundant number representation systems.

Advancing System Performance with Redundancy: From Biological to Artificial Designs.

Redundancy is a fundamental characteristic of many biological processes such as those in the genetic, visual, muscular, and nervous systems, yet its driven mechanism has not been fully comprehended. Until recently, the only understanding of redundancy is as a mean to attain fault tolerance, which is reflected in the design of many man-made systems. On the contrary, our previous work on redundant sensing (RS) has demonstrated an example where redundancy can be engineered solely for enhancing accuracy and precision. The design was inspired by the binocular structure of human vision, which we believe may share a similar operation. In this letter, we present a unified theory describing how such utilization of redundancy is feasible through two complementary mechanisms: representational redundancy (RPR) and entangled redundancy (ETR). We also point out two additional examples where our new understanding of redundancy can be applied to justify a system's superior performance. One is the human musculoskeletal system (HMS), a biological instance, and the other is the deep residual neural network (ResNet), an artificial counterpart. We envision that our theory would provide a framework for the future development of bio-inspired redundant artificial systems, as well as assist studies of the fundamental mechanisms governing various biological processes.

Dual theories: ‘Same but different’ or ‘different but same’?

I argue that, underneath the glitz, dual theories are simply examples of theoretically equivalent descriptions of the same underlying physical content: I distinguish them from cases of genuine underdetermination on the grounds that there is no real incompatibility involved between the descriptions. The incompatibility is at the level of purely unphysical structure. I argue that dual pairs are in fact very strongly analogous to gauge-related solutions even for dual pairs that look the most radically distinct, such as AdS/CFT. However, again by analogy with gauge freedom, I conjecture that dualities always point to a more fundamental (intrinsic) description, namely that in which the representational redundancy is eliminated.

Optimal (short-term) pump schedule detection for water distribution systems by neutral evolutionary search

The application of neutrality is a straightforward tool to preserve population diversity since it allows the genotype (on the represented search space) to be changed without affecting the corresponding fitness. To implement neutrality the literature suggests representational redundancy (more to one correspondence in genotype–phenotype mapping) although using it as a source of neutrality researchers uniformly reported better or worse results. Instead of applying representational redundancy here the utilization of pseudo redundancy as the source of neutrality is proposed, that is, neutrality is achieved by simple objective-fitness transformation while pseudo redundancy (as another redundancy interpretation) denotes more to one correspondence between objective-fitness domains by objective-fitness mapping. The contribution of this work is specified by the dynamic generational gap model introduced for evolutionary algorithms which appears when elitist strategy is used under neutrality by pseudo redundancy. This paper investigates the influence of dynamic generational gap model on the performance of a micro-genetic algorithm framework applied to achieve least cost water pump control policy for an industrial size water network distribution system. The presented constrained mixed-integer optimization problem is originated from the regional water network of the city of Sopron (60,000 citizens) located in Hungary. Here, the goal is to obtain intra-day pump schedule which minimizes the cost required for operation while satisfies the system constraints (water reservoir level limitations, pump flow and delivery regulations, pump energy consumption limitations) and fulfills the water requirement by the users.

Neutral Search Technique for Short-Term Pump Schedule Optimization

This paper deals with the computation of short-term (typically 1 day ) least-cost pump schedule for water distribution systems with on-off type pumps and well-defined operating points. The objective function is to minimize the overall energy charge for a prescribed water consumption while several constraints are considered, such as storage and source limitations, pump setting bounds, nodal mass balances, and the power demand charge. In this study a neutral search technique with genetic algorithms (GAs) is proposed to solve the least-cost pump schedule problem where neutrality is achieved through objective-fitness mapping instead of representational redundancy. We introduce a fitness assignment technique for groups of individuals where grouping is based on objective similarity. As a consequence two different individuals can be equally fit (belonging to the same group) which implies the neutrality. We compare the neutral search technique to two conventional GA approaches on a hypothetical water distribution...

Redundancy in model specifications for discrete event simulation

Although redundancy in model specification generally has negative connotations, we offer arguments for revising those convictions. Defining “representational redundancy” as the inclusion of any symbols not required to fulfill the study objectives, we cite several sources of redundancy, classified as accidental or intentional, that contribute positively to the model development tasks. Comparative benefits and detriments are discussed briefly. Focusing on the most interesting source of redundancy‐that which is intentionally induced by a modeling methodology—we demonstrate that automated elimination of redundancy can actually improve model execution time. Using four models drawn from the literature that are easily understood, but which represent some differences in size and complexity, the direct graphical representations shows improvements over a base case ranging from 27.3 percent to 68.1 percent in execution time. Further, increasing improvement is realized with increasing model size and complexity. These results are encouraging because they suggest that modeling methodologies with automated model diagnosis can significantly reduce both execution and developments time and cost.

Repetitive bibliographical information in relational databases

Bibliographical databases frequently have a few long, repetitive strings such as the recurring names of voluminous authors. Potter [Library Trends. 30(1): 21–39; 1981] observed this characteristic of bibliographical databases in his sample from the University of Illinois library catalog. This article presents a solution to the problem of loading repetitive bibliographical information in a microcomputer-based relational database-management system. Normalization theory does not explicitly address the characteristics of bibliographical relational databases. The representational redundancy design saves space in relational database tables by removing long, frequently occurring strings to separate tables where they can be referenced by shorter surrogates in a main table. This design was suggested by some reflections by Kent (Data and Reality, Basic Assumptions in Data Processing Reconsidered. Amsterdam: North-Holland; 1978) and by the example of MERLIN [Program. 10(4): 123–134; 1976]. Telephone-book data and the library-catalog data of Potter was used to illustrate the economies achieved in representing repetitive bibliographical information in relational databases. © 1988 John Wiley & Sons, Inc.

On Phonetic and Phonemic Mnemonic Systems: A Reply to M. J. Dickel

Dickel (1983) compared the effectiveness of the phonetic and the phonemic systems in terms of his three stated principles of encoding mnemonics, namely, recoding, meaningfulness, and organization, and concluded that, in general, the phonetic system is more effective than the phonemic system. In this reply, recoding, involving the encoding-storage-decoding sequence, was considered a fundamental memory operation in mnemonics, whose effectiveness depends on reduction of representational redundancy, on meaningfulness, and on organization. It was shown that the effectiveness of the phonetic system is based primarily on the reduction of redundancy, while the meaningfulness and organization favor the phonetic system. If the recall measure of performance is considered, Dickel's claims have some merit though they are highly hypothetical. Because encoding pathways are multiple, the phonetic system was shown not to be applicable to memory-recognition tasks, while no such limitation is apparent in case of the phonemic recoding system. Some methodological problems of mnemonics testing were considered.