Cognitive Navigation for Intelligent Mobile Robots:A Learning-Based Approach With Topological Memory Configuration

Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial memory.In this paper,we propose a learning-based visual navigation pipeline that uses topological maps as memory configurations.We introduce a unique online topology construction approach that fuses odometry pose estimation and perceptual similarity estimation.This tackles the issues of topological node redundancy and incorrect edge connections,which stem from the distribution gap between the spatial and perceptual domains.Furthermore,we propose a differentiable graph extraction structure,the topology multi-factor transformer(TMFT).This structure utilizes graph neural networks to integrate global memory and incorporates a multi-factor attention mechanism to underscore elements closely related to relevant target cues for policy generation.Results from photorealistic simulations on image-goal navigation tasks highlight the superior navigation performance of our proposed pipeline compared to existing memory structures.Comprehensive validation through behavior visualization,interpretability tests,and real-world deployment further underscore the adapt-ability and efficacy of our method.

Topological Anosov Maps of Non-compact Metric Spaces

Let X be a metric space. We say that a continuous surjection f:X→X is a topological Anosov map (abbrev. TA map) if f is expansive and has pseudo orbit tracing property with respect to some compatible metric for X . This paper studies the properties of TA maps of non compact metric spaces and gives some conditions for the map to be topologically mixing.

INVERSE KINEMATICS FOR A 6 DOF MANIPULATOR BASED ON NEURAL NETWORK

A methodology is presented whereby a neural network is used to learn the inverse kinematic relationships of the position and orientation of a six joint manipulator. The arm solution for the orientation of a manipulator using a self organizing neural net is studied in this paper. A new training model of the self organizing neural network is proposed by thoroughly studying Martinetz, Ritter and Schulten′s self organizing neural network based on Kohonen′s self organizing mapping algorithm using a Widrow Hoff type error correction rule and closely combining the characters of the inverse kinematic relationship for a robot arm. The computer simulation results for a PUMA 560 robot show that the proposed method has a significant improvement over other methods documented in the references in self organizing capability and precision by training process.

Localization and navigation using a novel artificial landmark for indoor mobile robots

This paper presents a practical topological navigation system for indoor mobile robots, making use of a novel artificial landmark which is called MR code. This new kind of paper-made landmarks earl be easi- ly attached on the ceilings or on the walls, lmealization algorithms for the two cases are given respective- ly. A docking control algorithm is also described, which a robot employs to approach its current goal. A simple topological navigation algorithm is proposed. Experiment results show the effectiveness of the method in real environment.

THE ORBIT SHIFT TOPOLOGICAL STABILITY OF ANOSOV MAPS

It is shown that Anosov maps are orbit shift topologically stable.

ERRATUM A TOPOLOGICALLY MIXING MAP WITH TRIVIAL ROTATION SET

We showed in [G. H], if f is a Cr-topologically mixing map of the circle (r ≥0),then its rotation set will be non-trivial. But this statement is only satisfied for generic(open and dense) subset of all Cr-topologically mixing maps of the circle (r≥0). Here,we present another proof of the above statement. Moreover, we introduce a topologicallymixing map of the circle with trivial rotation set.

OHTMA:an optimized heuristic topology-aware mapping algorithm on the Tianhe-3 exascale supercomputer prototype

With the rapid increase of the size of applications and the complexity of the supercomputer architecture,topology-aware process mapping becomes increasingly important.High communication cost has become a dominant constraint of the performance of applications running on the supercomputer.To avoid a bad mapping strategy which can lead to terrible communication performance,we propose an optimized heuristic topology-aware mapping algorithm(OHTMA).The algorithm attempts to minimize the hop-byte metric that we use to measure the mapping results.OHTMA incorporates a new greedy heuristic method and pair-exchange-based optimization.It reduces the number of long-distance communications and effectively enhances the locality of the communication.Experimental results on the Tianhe-3 exascale supercomputer prototype indicate that OHTMA can significantly reduce the communication costs.

Lattice-valued Semicontinuous Mappings and Induced Topologies

Lattice-valued semicontinuous mappings play a basic and important role in solving the problems of L-fuzzy compactification theory,and make the previous work on weakly induced spaces and induced spaces determinatively generalized and strengthened.Moreover,we can describe the complete distributivity of lattices with them as well.In this paper,we give the mutually descrip- tive relation between lattice-valued semicontinuous mappings and the complete distributivity of lattices, and the construction theorems of open sets and closed sets in lattice-valued fully stratified spaces, weakly induced spaces and induced spaces(they are called S-spaces).Furthermore,we will investi- gate the structure of the co-topology of S-space,solve a series of interesting problems on product, N-compactness and metrization of S-spaces.

CHAOS FOR MIXING TRANSFORMATIONS

For a class of mixing transformations of a compact metric space it is proved that each chaoticsubset is'small' but the possibility for any finite subset to display chaotic behavior is 'large'.

Strongly Gauduchon Spaces

The authors define strongly Gauduchon spaces and the class JG, which aregeneralization of strongly Gauduchon manifolds in complex spaces. Comparing with the case of Kohlerian, the strongly Gauduchon space and the class JG are similar to the Kohler space and the Fujiki class L respectively. Some properties about these complex spaces are obtained. Moreover, the relations between the strongly Gauduchon spaces and the class JG are studied.