An autonomous rendezvous and docking system using cruise missile technologies

In November 1990 the Autonomous Rendezvous & Docking (AR&D) system was first demonstrated for members of NASA's Strategic Avionics Technology Working Group. This simulation utilized prototype hardware from the Cruise Missile and Advanced Centaur Avionics systems. The object was to show that all the accuracy, reliability and operational requirements established for a space craft to dock with Space Station Freedom could be met by the proposed system. The rapid prototyping capabilities of the Advanced Avionics Systems Development Laboratory were used to evaluate the proposed system in a real time, hardware in the loop simulation of the rendezvous and docking reference mission. The simulation permits manual, supervised automatic and fully autonomous operations to be evaluated. It is also being upgraded to be able to test an Autonomous Approach and Landing (AA&L) system. The AA&L and AR&D systems are very similar. Both use inertial guidance and control systems supplemented by GPS. Both use an Image Processing System (IPS), for target recognition and tracking. The IPS includes a general purpose multiprocessor computer and a selected suite of sensors that will provide the required relative position and orientation data. Graphic displays can also be generated by the computer, providing the astronaut / operator with real-time guidance and navigation data with enhanced video or sensor imagery

POMDP solving: what rewards do you really expect at execution?

Partially Observable Markov Decision Processes have gained an increasing interest in many research communities, due to sensible improvements of their optimization algorithms and of computers capabilities. Yet, most research focus on optimizing either average accumulated rewards (AI planning) or direct entropy (active perception), whereas none of them matches the rewards actually gathered at execution. Indeed, the first optimization criterion linearly averages over all belief states, so that it does not gain best information from different observations, while the second one totally discards rewards. Thus, motivated by simple demonstrative examples, we study an additive combination of these two criteria to get the best of reward gathering and information acquisition at execution. We then compare our criterion with classical ones, and highlight the need to consider new hybrid non-linear criteria, on a realistic multi-target recognition and tracking mission

Multimodal Subspace Support Vector Data Description

In this paper, we propose a novel method for projecting data from multiple modalities to a new subspace optimized for one-class classification. The proposed method iteratively transforms the data from the original feature space of each modality to a new common feature space along with finding a joint compact description of data coming from all the modalities. For data in each modality, we define a separate transformation to map the data from the corresponding feature space to the new optimized subspace by exploiting the available information from the class of interest only. We also propose different regularization strategies for the proposed method and provide both linear and non-linear formulations. The proposed Multimodal Subspace Support Vector Data Description outperforms all the competing methods using data from a single modality or fusing data from all modalities in four out of five datasets.Comment: 26 pages manuscript (6 tables, 2 figures), 24 pages supplementary material (27 tables, 10 figures). The manuscript and supplementary material are combined as a single .pdf (50 pages) fil

Haris: an Advanced Autonomous Mobile Robot for Smart Parking Assistance

This paper presents Haris, an advanced autonomous mobile robot system for tracking the location of vehicles in crowded car parks using license plate recognition. The system employs simultaneous localization and mapping (SLAM) for autonomous navigation and precise mapping of the parking area, eliminating the need for GPS dependency. In addition, the system utilizes a sophisticated framework using computer vision techniques for object detection and automatic license plate recognition (ALPR) for reading and associating license plate numbers with location data. This information is subsequently synchronized with a back-end service and made accessible to users via a user-friendly mobile app, offering effortless vehicle location and alleviating congestion within the parking facility. The proposed system has the potential to improve the management of short-term large outdoor parking areas in crowded places such as sports stadiums. The demo of the robot can be found on https://youtu.be/ZkTCM35fxa0?si=QjggJuN7M1o3oifx.Comment: Accepted in 2024 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA, 202

Super-Resolution Enhancement of Digital Video

SR from digital video is a relatively new field, in only its third decade of existence. There is no doubt that as imaging sensor technologies, optical fabrication techniques, and computational algorithms mature, SR will find its way into digital video products such as cameras and digital cable set-top boxes. These papers on the fundamental SR topics of image registration, regularization, photometric diversity, detector nonuniformity, compression, optical design, and performance metrics serve as pioneers in the dynamic and evolving field of SR image reconstruction research and development. We are proud to present them to the image and video processing research community. (Refers to papers appearing in the same issue of the EURASIP Journal on Advances in Signal Processing in which this editorial appeared.

Implementation of Vision Based Robot Navigation System in Dynamic Environment

In this paper the implementation of robot navigation in the dynamic environment using vision based approach is proposed. Vision based robot navigation has been a fundamental goal in both robotics and computer vision research. In the visual guidelines based navigation system, the motion instructions required to control the robot can be inferred directly from the acquired images. In this work, the algorithm is designed for an intelligent robot which is placed in an unknown environment. The robot detects the signs from a captured images using features based extraction and moves according to the signs. Also, it is able to tackle an encountered obstacle in its way. The robot successfully detects different signs like right, left and stop from an image. DOI: 10.17762/ijritcc2321-8169.15065

SETHI / RAMSES-NG: New performances of the flexible multi-spectral airborne remote sensing research platform

International audienceSETHI is an airborne SAR/GMTI system developed by the French Aerospace Lab. ONERA, and integrating various sensors. In 2016 ONERA invested in upgrade and improvement of all SETHI components. The microwave ones cover from VHF-UHF to X Band, full polarimetric and very high resolution, along track and cross track interferometry and very high precision multi-baseline capacity for interferometry and tomography applications. The optronic sensors offer very high spatial resolution visible images and fine spectral scene analysis in VNIR and SWIR bands. This paper presents the upgrade and new performances of this flexible platform and the qualification campaign results with various sensor configurations