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Localizing global descriptors for content-based image retrieval
TLDR
The proposed descriptors manage to outperform common SIFT- and SURF-based approaches while they perform comparably, if not better, against recent state-of-the-art methods that base their success on much more complex data manipulation.
DARP: Divide Areas Algorithm for Optimal Multi-Robot Coverage Path Planning
TLDR
The proposed technique transforms the original integer programming problem (mCPP) into several single-robot problems (CPP), the solutions of which constitute the optimal mCPP solution, alleviating the original m CPP explosive combinatorial complexity.
Searching images with MPEG-7 (& MPEG-7-like) Powered Localized dEscriptors: The SIMPLE answer to effective Content Based Image Retrieval
TLDR
An astonishing boost in the retrieval performance of the proposed descriptors is revealed compared both to their own performance and to other state-of-the-art methods of local and global descriptors.
MarsExplorer: Exploration of Unknown Terrains via Deep Reinforcement Learning and Procedurally Generated Environments
TLDR
A study on the performance curves revealed that PPO-based policy was capable of performing adaptive-to-the-unknown-terrain sweeping without leaving expensive- to-revisit areas uncovered, underlying the capability of RL-based methodologies to tackle exploration tasks efficiently.
Real-time adaptive multi-robot exploration with application to underwater map construction
TLDR
The combination of the transformed optimization criterion with CAO results in a multi-AXV exploration scheme which is both practically implementable and provides with quite efficient solutions as it is shown both by theoretical analysis and by extensive simulation experiments and real-life underwater sea-floor mapping experiments in the Leixes port, Portugal.
A distributed, plug-n-play algorithm for multi-robot applications with a priori non-computable objective functions
TLDR
A distributed methodology based on the cognitive-based adaptive optimization (CAO) algorithm, that is able to approximate the evolution of each robot’s cost function and to adequately optimize its decision variables (robot actions), that shares the same convergence characteristics as block coordinate descent algorithms.
Continuously informed heuristic A∗-optimal path retrieval inside an unknown environment
TLDR
This paper proposes a specifically-tailored variation (CIA∗) of the A∗ algorithm that inherits the A ∗ optimality and efficiency guarantees, while at the same time exploits the learnt formation of the obstacles, to on-line revise the heuristic evaluation of the candidate states.
Towards an Integrated Low-Cost Agricultural Monitoring System with Unmanned Aircraft System
TLDR
This paper presents a practically oriented application on vineyards towards an integrated low-cost system which utilizes Spiral-STC (Spanning Tree Coverage) algorithm as a Coverage Path Planning (CPP) method.
The NOPTILUS project: Autonomous Multi-AUV Navigation for Exploration of Unknown Environments
TLDR
A new approach is presented that is able to efficiently and fully-autonomously navigate a team of AUVs when deployed in exploration of unknown static and dynamic environments towards providing accurate static/dynamic maps of the environment.
Autonomous and Cooperative Design of the Monitor Positions for a Team of UAVs to Maximize the Quantity and Quality of Detected Objects
TLDR
The experimental evaluation indicates that the proposed navigation algorithm was able to consistently navigate the swarm of UAVs to “strategic” monitoring positions and also adapt to the different number of swarm sizes.
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