A Novel Model for Driver Lane Change Prediction in Cooperative Adaptive Cruise Control Systems

Accurate lane change prediction can reduce potential accidents and contribute to higher road safety. Adaptive cruise control (ACC), lane departure avoidance (LDA), and lane keeping assistance (LKA) are some conventional modules in advanced driver assistance systems (ADAS). Thanks to vehicle-to-vehicle communication (V2V), vehicles can share traffic information with surrounding vehicles, enabling cooperative adaptive cruise control (CACC). While ACC relies on the vehicle's sensors to obtain the position and velocity of the leading vehicle, CACC also has access to the acceleration of multiple vehicles through V2V communication. This paper compares the type of information (position, velocity, acceleration) and the number of surrounding vehicles for driver lane change prediction. We trained an LSTM (Long Short-Term Memory) on the HighD dataset to predict lane change intention. Results indicate a significant improvement in accuracy with an increase in the number of surrounding vehicles and the information received from them. Specifically, the proposed model can predict the ego vehicle lane change with 59.15% and 92.43% accuracy in ACC and CACC scenarios, respectively

RoboCup Soccer Leagues

RoboCup was created in 1996 by a group of Japanese, American, and European Artificial Intelligence and Robotics researchers with a formidable, visionary long-term challenge: “By 2050 a team of robot soccer players will beat the human World Cup champion team.” At that time, in the mid 90s, when there were very few effective mobile robots and the Honda P2 humanoid robot was presented to a stunning public for the first time also in 1996, the RoboCup challenge, set as an adversarial game between teams of autonomous robots, was fascinating and exciting. RoboCup enthusiastically and concretely introduced three robot soccer leagues, namely “Simulation,” “Small-Size,” and “Middle-Size,” as we explain below, and organized its first competitions at IJCAI’97 in Nagoya with a surprising number of 100 participants [RC97]. It was the beginning of what became a continously growing research community. RoboCup established itself as a structured organization (the RoboCup Federation www.RoboCup.org). RoboCup fosters annual competition events, where the scientific challenges faced by the researchers are addressed in a setting that is attractive also to the general public. and the RoboCup events are the ones most popular and attended in the research fields of AI and Robotics.RoboCup further includes a technical symposium with contributions relevant to the RoboCup competitions and beyond to the general AI and robotics

Data fusion using ultra wideband time-of-flight positioning for mobile robot applications

Self-localization of a robot is one of the most important requirements in mobile robotics. There are several approaches to providing localization data. The Ultra Wide Band Time of Flight provides position information but lacks the angle. Odometry data can be combined by using a data fusion algorithm. This paper addresses the application of data fusion algorithms based on odometry and Ultra Wide Band Time of Flight positioning using a Kalman filter that allows performing the data fusion task which outputs the position and orientation of the robot. The proposed solution, validated in a real developed platform can be applied in service and industrial robots.he authors are grateful to the Foundation for Sci- ence and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021). This work has been supported by NORTE- 01-0247-FEDER-072598 iSafety: Intelligent system for occu- pational safety and well-being in the retail sector. The authors also want to thank CEFET-RJ and FAPERJ.info:eu-repo/semantics/publishedVersio

OPTIMAL PITCH MAP GENERATION FOR SCANNING PITCH DESIGN IN SELECTIVE SAMPLING

The reverse engineering process represents one of the best known methodologies for creating three-dimensional (3D) virtual models starting from physical ones. Even if in the last few years its usage has significantly increased, the remarkable involvement of the operator has until now represented a significant constraint for its growth. Having regard to the fact that this process, and in particular its first step (that is the acquisition phase), strongly depends on the operator's ability and expertise, this paper aims at proposing a strategy for automatically supporting an "optimal" acquisition phase. Moreover, the acquisition phase represents the only moment in which there is a direct contact between the virtual model and the physical model. For this reason, designing an "optimal" acquisition phase will provide as output an efficient set of morphological data, which will turn out to be extremely useful for the following reverse engineering passages (pre-processing, segmentation, fitting, …). This scenario drives the researcher to use a selectivesampling plan, whose grid dimensions are correlated with the complexity of the local surface region analyzed, instead of a constant one. As a consequence, this work proposes a complete operative strategy which, starting from a first raw preliminary acquisition, will provide a new selectivesampling plan during the acquisition phase, in order to allow a deeper and more efficient new scansion. The proposed solution does not require the creation of any intermediate model and relies exclusively on the analysis of the metrological performances of the 3D scanner device and of the morphological behaviour of the surface acquired

Sensory systems in micro-processor controlled prosthetic leg: a review

Micro-processor controlled prosthetic legs (MPCPL) offer better functionality than conventional prosthetic legs as they use actuators to replace missing joint function. This potentially reduces the user's metabolic energy consumption and normal walking gait can be mimicked as closely as possible. However, MPCPL require a good control system to perform efficiently, and one of the essential components is the system of sensors. The sensory system must satisfy two important criteria; the practicality in donning and doffing the prosthesis, i.e. the process of putting on and taking off the prosthesis by the amputee user, and the quality in the information provided. In this paper, a comprehensive review was conducted on studies related to the state of the art of sensory system adopted in MPCPL. The publications were searched using four electronics databases within the last 13 years. A total of 31 papers were reviewed. The articles were classified into three main categories: prosthetic-device oriented, user's-biological-input oriented and neuro-mechanical fusion sensory system. Types of sensors used and their application to the prosthetic system were analyzed. This review indicates that the sensors technology reported in the literature still does not fulfil the criteria of an efficient sensory system. Hence, a sensory system that eases the don and doff process of the prosthesis, yet informative in terms of providing enough useful data to effectively control the prosthesis, is needed for a successful MPCPL

A Novel Model for Driver Lane Change Prediction in Cooperative Adaptive Cruise Control Systems

Accurate lane change prediction can reduce potential accidents and contribute to higher road safety. Adaptive cruise control (ACC), lane departure avoidance (LDA), and lane keeping assistance (LKA) are some conventional modules in advanced driver assistance systems (ADAS). Thanks to vehicle-to-vehicle communication (V2V), vehicles can share traffic information with surrounding vehicles, enabling cooperative adaptive cruise control (CACC). While ACC relies on the vehicle's sensors to obtain the position and velocity of the leading vehicle, CACC also has access to the acceleration of multiple vehicles through V2V communication. This paper compares the type of information (position, velocity, acceleration) and the number of surrounding vehicles for driver lane change prediction. We trained an LSTM (Long Short-Term Memory) on the HighD dataset to predict lane change intention. Results indicate a significant improvement in accuracy with an increase in the number of surrounding vehicles and the information received from them. Specifically, the proposed model can predict the ego vehicle lane change with 59.15% and 92.43% accuracy in ACC and CACC scenarios, respectively

A novel trigger-based method for hydrothermal vents prospecting using an autonomous underwater robot

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Autonomous Robots 29 (2010): 67-83, doi:10.1007/s10514-010-9187-y.In this paper we address the problem of localizing active hydrothermal vents on the seafloor using an Autonomous Underwater Vehicle (AUV). The plumes emitted by hydrothermal vents are the result of thermal and chemical inputs from submarine hot spring systems into the overlying ocean. The Woods Hole Oceanographic Institution's Autonomous Benthic Explorer (ABE) AUV has successfully localized previously undiscovered hydrothermal vent fields in several recent vent prospecting expeditions. These expeditions utilized the AUV for a three-stage, nested survey strategy approach (German et al., 2008). Each stage consists of a survey flown at successively deeper depths through easier to detect but spatially more constrained vent fluids. Ideally this sequence of surveys culminates in photographic evidence of the vent fields themselves. In this work we introduce a new adaptive strategy for an AUV's movement during the first, highest-altitude survey: the AUV initially moves along pre-designed tracklines but certain conditions can trigger an adaptive movement that is likely to acquire additional high value data for vent localization. The trigger threshold is changed during the mission, adapting the method to the different survey profiles the robot may find. The proposed algorithm is vetted on data from previous ABE missions and measures of efficiency presented

Experimental Study of the Biped Walking Robot Applying a Gravity Compensator

In this paper, KUBIR 4(the name of a robot) which is a lower body of the humanoid robot applying a gravity compensator was developed. KUBIR 4 has 13 DOF, 1 DOF in waist and 12 DOF in legs. Its weight is 62kg and height is 91cm. Also, for the control for the robot, a control system developed. The control system is composed of a distributed control system where host PC is applied as a master controller and a TMS320c2408 microprocessor as a joint motor motion controller. A GUI program for easy control of robot motion was developed where payloads of each joint and joint motor’s currents are displayed in real time. Walking experiments were performed to verify the superior performance of the robot applying the gravity compensator. For this, the gravity compensator was applied to only left knee and coxa joint to compare with right leg. Same experiments were performed on both legs and their results showed that total current consumption and the maximum load of the left leg joints were less than those of the right leg.제 1 장 서론 1 제 2 장 중력보상기 적용한 이족보행로봇의 기구부 구성 3 2.1 중력보상기 구성 및 역학 해석 3 2.1.1 중력보상기 구성 3 2.1.2 중력보상기의 역학 해석 4 2.2 이족보행로봇의 기구부 구성 7 2.2.1 전체 시스템 구성 7 2.2.2 관절 기구부 구성 9 2.2.3 관절 구동기 사양 14 제 3 장 중력보상기 적용한 이족보행로봇의 기구학 해석 15 3.1 D-H 규약을 통한 기구학 해석 15 제 4 장 중력보상기 적용한 이족보행로봇의 제어시스템 구성 22 4.1 전체 시스템 구성 22 4.2 DC 모터 모션 컨트롤러 24 4.3 모션 제어 알고리즘 27 4.4 로봇 모션 컨트롤 프로그램 31 제 5 장 중력보상기 적용한 이족보행로봇의 실험 및 고찰 35 5.1 실험 내용 35 5.2 실험 결과 및 고찰 41 5.2.1 실험1 한발 들고 무릎 굽혔다 펴기 42 5.2.2 실험2 동일한 시간의 모션 동작으로 정적 보행 46 5.2.3 실험3 모션 시간 및 딜레이 시간을 조정한 정적 보행 51 제 6 장 결론 56 참고문헌 5

Mobile robot path planning by means of ant algorithms

Tato práce se zabývá plánováním cesty robota při použití algoritmů pro optimalizaci pomocí mravenčích kolonií. Teoretická část práce uvádí základní pojmy z problematiky plánování cesty robota. Dále se teoretická část věnuje mravenčím algoritmům coby nástrojům pro optimalizaci a plánování cesty robota. Praktická část práce se zabývá návrhem a implementací mravenčích algoritmů pro plánování cesty robota v jazyce Java.This thesis deals with robot path planning by means of ant colony optimization algorithms. The theoretical part of this thesis introduces basics of path planning problematics. The theoretical part either deals with ant algorithms as optimization and path planning tools. The practical part deals with design and implementation of path planning by means of ant algorithms in Java language.

Intégration et évaluation de capacités interactives d'un robot humanoïde

Le domaine de l'Interaction Humain-Robot (HRI) est en pleine expansion. En effet, de plus en plus de plateformes robotiques sont mises en oeuvre pour faire évoluer ce domaine. Sur ces plateformes, toujours plus de modalités d'interaction sont mises en place telles que les mouvements corporels, la reconnaissance de gestes ou d'objets, la reconnaissance et la synthèse vocale ou encore la mobilité, pour pouvoir effectuer l'interaction la plus complète et la plus naturelle pour l'humain. Mais ceci amène aussi une complexité croissante de l'intégration de ces modalités sur une seule et même plateforme. Aussi, le domaine HRI étant à ses débuts, la méthodologie expérimentale des travaux se limite le plus souvent à des preuves de concept éprouvées en laboratoire ou en milieux ouverts non contrôlés. Il se trouve que peu de chercheurs présentent une démarche structurée et rigoureuse pour l'évaluation expérimentale d'interaction humain-robot en milieux ouverts, et il en résulte des recherches de types exploratoires qui examinent principalement la complexité technologique des modalités interactives à mettre en oeuvre, et non l'impact de ces modalités sur la qualité des interactions. Le but de l'étude présentée dans ce document est d'étudier l'intégration de plusieurs modalités interactives sur un robot mobile humanoïde telles que la parole, les gestes et la mobilité sur la qualité des interactions humain-robot. Plus spécifiquement, le contexte de l'étude consiste à examiner l'impact de modalités interactives sur la capacité du robot à attirer l'attention d'une personne et à engager une interaction avec elle. Le scénario expérimental consiste à permettre au robot, à partir de la parole, d'expressions faciales, de mouvement de la tête, de gestes avec son bras et de sa mobilité, de demander de l'assistance à une personne à proximité de lui remettre un objet se trouvant au sol. L'hypothèse sous-jacente est que l'intégration de l'ensemble de ces modalités devrait améliorer la capacité du robot à engager des personnes à interagir avec lui. Des expérimentations ont été faites en milieu contrôlé et non-contrôlé selon deux protocoles expérimentaux : une étude des modalités à l'intérieur d'une population, et une étude de variation entre individus. D'une manière générale, il en ressort que l'ajout de modalités améliore la qualité de l'engagement de l'interaction par le robot, mais qu'il faut porter une attention particulière à l'approche de la personne par le robot, principalement pour les personnes non familières avec ce dernier. De plus, les observations indiquent qu'il est plus facile d'obtenir des résultats significatifs en environnement contrôlé, elles permettent d'identifier des pistes d'amélioration pour éventuellement arriver à en obtenir en milieu non-contrôlé. Enfin, ce premier projet d'intégration et d'évaluation de capacités interactives d'un robot mobile servira à alimenter une prochaine itération avec un robot plus sophistiqué présentement en conception