19,233 research outputs found
Assistive trajectories for human-in-the-loop mobile robotic platforms
Autonomous and semi-autonomous smoothly interruptible trajectories are developed which are highly suitable for application in tele-operated mobile robots, operator on-board military mobile ground platforms, and other mobility assistance platforms. These trajectories will allow a navigational system to provide assistance to the operator in the loop, for purpose built robots or remotely operated platforms. This will allow the platform to function well beyond the line-of-sight of the operator, enabling remote operation inside a building, surveillance, or advanced observations whilst keeping the operator in a safe location. In addition, on-board operators can be assisted to navigate without collision when distracted, or under-fire, or when physically disabled by injury
Tahap penguasaan, sikap dan minat pelajar Kolej Kemahiran Tinggi MARA terhadap mata pelajaran Bahasa Inggeris
Kajian ini dilakukan untuk mengenal pasti tahap penguasaan, sikap dan minat pelajar
Kolej Kemahiran Tinggi Mara Sri Gading terhadap Bahasa Inggeris. Kajian yang
dijalankan ini berbentuk deskriptif atau lebih dikenali sebagai kaedah tinjauan. Seramai
325 orang pelajar Diploma in Construction Technology dari Kolej Kemahiran Tinggi
Mara di daerah Batu Pahat telah dipilih sebagai sampel dalam kajian ini. Data yang
diperoleh melalui instrument soal selidik telah dianalisis untuk mendapatkan
pengukuran min, sisihan piawai, dan Pekali Korelasi Pearson untuk melihat hubungan
hasil dapatan data. Manakala, frekuensi dan peratusan digunakan bagi mengukur
penguasaan pelajar. Hasil dapatan kajian menunjukkan bahawa tahap penguasaan
Bahasa Inggeris pelajar adalah berada pada tahap sederhana manakala faktor utama yang
mempengaruhi penguasaan Bahasa Inggeris tersebut adalah minat diikuti oleh sikap.
Hasil dapatan menggunakan pekali Korelasi Pearson juga menunjukkan bahawa terdapat
hubungan yang signifikan antara sikap dengan penguasaan Bahasa Inggeris dan antara
minat dengan penguasaan Bahasa Inggeris. Kajian menunjukkan bahawa semakin positif
sikap dan minat pelajar terhadap pengajaran dan pembelajaran Bahasa Inggeris semakin
tinggi pencapaian mereka. Hasil daripada kajian ini diharapkan dapat membantu pelajar
dalam meningkatkan penguasaan Bahasa Inggeris dengan memupuk sikap positif dalam
diri serta meningkatkan minat mereka terhadap Bahasa Inggeris dengan lebih baik. Oleh
itu, diharap kajian ini dapat memberi panduan kepada pihak-pihak yang terlibat dalam
membuat kajian yang akan datang
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Simultaneous Localization and Mapping (SLAM)consists in the concurrent
construction of a model of the environment (the map), and the estimation of the
state of the robot moving within it. The SLAM community has made astonishing
progress over the last 30 years, enabling large-scale real-world applications,
and witnessing a steady transition of this technology to industry. We survey
the current state of SLAM. We start by presenting what is now the de-facto
standard formulation for SLAM. We then review related work, covering a broad
set of topics including robustness and scalability in long-term mapping, metric
and semantic representations for mapping, theoretical performance guarantees,
active SLAM and exploration, and other new frontiers. This paper simultaneously
serves as a position paper and tutorial to those who are users of SLAM. By
looking at the published research with a critical eye, we delineate open
challenges and new research issues, that still deserve careful scientific
investigation. The paper also contains the authors' take on two questions that
often animate discussions during robotics conferences: Do robots need SLAM? and
Is SLAM solved
Human-Machine Interface for Remote Training of Robot Tasks
Regardless of their industrial or research application, the streamlining of
robot operations is limited by the proximity of experienced users to the actual
hardware. Be it massive open online robotics courses, crowd-sourcing of robot
task training, or remote research on massive robot farms for machine learning,
the need to create an apt remote Human-Machine Interface is quite prevalent.
The paper at hand proposes a novel solution to the programming/training of
remote robots employing an intuitive and accurate user-interface which offers
all the benefits of working with real robots without imposing delays and
inefficiency. The system includes: a vision-based 3D hand detection and gesture
recognition subsystem, a simulated digital twin of a robot as visual feedback,
and the "remote" robot learning/executing trajectories using dynamic motion
primitives. Our results indicate that the system is a promising solution to the
problem of remote training of robot tasks.Comment: Accepted in IEEE International Conference on Imaging Systems and
Techniques - IST201
Redundant neural vision systems: competing for collision recognition roles
Ability to detect collisions is vital for future robots that interact with humans in complex visual environments. Lobula giant movement detectors (LGMD) and directional selective neurons (DSNs) are two types of identified neurons found in the visual pathways of insects such as locusts. Recent modelling studies showed that the LGMD or grouped DSNs could each be tuned for collision recognition. In both biological and artificial vision systems, however, which one should play the collision recognition role and the way the two types of specialized visual neurons could be functioning together are not clear. In this modeling study, we compared the competence of the LGMD and the DSNs, and also investigate the cooperation of the two neural vision systems for collision recognition via artificial evolution. We implemented three types of collision recognition neural subsystems – the LGMD, the DSNs and a hybrid system which combines the LGMD and the DSNs subsystems together, in each individual agent. A switch gene determines which of the three redundant neural subsystems plays the collision recognition role. We found that, in both robotics and driving environments, the LGMD was able to build up its ability for collision recognition quickly and robustly therefore reducing the chance of other types of neural networks to play the same role. The results suggest that the LGMD neural network could be the ideal model to be realized in hardware for collision recognition
Uncalibrated Dynamic Mechanical System Controller
An apparatus and method for enabling an uncalibrated, model independent controller for a mechanical system using a dynamic quasi-Newton algorithm which incorporates velocity components of any moving system parameter(s) is provided. In the preferred embodiment, tracking of a moving target by a robot having multiple degrees of freedom is achieved using an uncalibrated model independent visual servo control. Model independent visual servo control is defined as using visual feedback to control a robot's servomotors without a precisely calibrated kinematic robot model or camera model. A processor updates a Jacobian and a controller provides control signals such that the robot's end effector is directed to a desired location relative to a target on a workpiece.Georgia Tech Research Corporatio
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