Mobile Robotics Integration in Introductory Undergraduate Engineering Courses

2016 ◽  
Author(s):  
Rafael V. Aroca ◽  
Flavio Y. Watanabe ◽  
Marcio T. De Avila ◽  
Andre C. Hernandes
Keyword(s):  
Mobile Robotics ◽  
Undergraduate Engineering

HOW STUDENTS DEFINE THEIR SUCCESS: A RESEARCH STUDY

2020 ◽  
Author(s):  
Max Ullrich ◽  
David S. Strong
Keyword(s):  
Pilot Study ◽  
Engineering Students ◽  
Research Study ◽  
Survey Instrument ◽  
Undergraduate Engineering ◽  
Diversity And Inclusion ◽  
Full Study ◽  
Definition Of Success ◽  
Definition Of ◽  
Diverse Groups

How undergraduate engineering students define their success and plan for their future differs notably amongst students. With a push for greater diversity and inclusion in engineering schools, it is valuable to also better understand the differences in these areas among different students to allow institutions to better serve the needs of these diverse groups.  The purpose of this research study is to explore students’ definition of success both in the present and projecting forward 5 to 10 years, as well as to understand to what level students reflect on, and plan for, the future. The proposed survey instrument for the pilot stage of this research includes 56 closed-ended questions and 3 open-ended questions. Evidence for the validity of the research instrument is established through a mixed-method pilot study. This paper will discuss the survey instrument, the pilot study, and outline plans for the full study.

Real-Time Support for Mobile Robotics

2005 ◽  
Author(s):  
Huan Li ◽  
John Sweeney ◽  
Krithi Ramamritham ◽  
Roderic Grupen ◽  
Prashant Shenoy
Keyword(s):  
Real Time ◽  
Mobile Robotics

scholarly journals The Role of Global Appearance of Omnidirectional Images in Relative Distance and Orientation Retrieval

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3327
Author(s):  
Vicente Román ◽  
Luis Payá ◽  
Adrián Peidró ◽  
Mónica Ballesta ◽  
Oscar Reinoso
Keyword(s):  
Mobile Robotics ◽  
A Priori ◽  
Computational Cost ◽  
Relevant Information ◽  
Local Features ◽  
New Family ◽  
Lighting Conditions ◽  
Omnidirectional Images ◽  
Great Development

Over the last few years, mobile robotics has experienced a great development thanks to the wide variety of problems that can be solved with this technology. An autonomous mobile robot must be able to operate in a priori unknown environments, planning its trajectory and navigating to the required target points. With this aim, it is crucial solving the mapping and localization problems with accuracy and acceptable computational cost. The use of omnidirectional vision systems has emerged as a robust choice thanks to the big quantity of information they can extract from the environment. The images must be processed to obtain relevant information that permits solving robustly the mapping and localization problems. The classical frameworks to address this problem are based on the extraction, description and tracking of local features or landmarks. However, more recently, a new family of methods has emerged as a robust alternative in mobile robotics. It consists of describing each image as a whole, what leads to conceptually simpler algorithms. While methods based on local features have been extensively studied and compared in the literature, those based on global appearance still merit a deep study to uncover their performance. In this work, a comparative evaluation of six global-appearance description techniques in localization tasks is carried out, both in terms of accuracy and computational cost. Some sets of images captured in a real environment are used with this aim, including some typical phenomena such as changes in lighting conditions, visual aliasing, partial occlusions and noise.

scholarly journals Efficient Reactive Obstacle Avoidance Using Spirals for Escape

Drones ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 51
Author(s):  
Fábio Azevedo ◽  
Jaime S. Cardoso ◽  
André Ferreira ◽  
Tiago Fernandes ◽  
Miguel Moreira ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Mobile Robotics ◽  
Point Clouds ◽  
Depth Camera ◽  
Main Task ◽  
Robust Method ◽  
Aerial Vehicles ◽  
Correct Execution ◽  
Low Altitude ◽  
High Degree

The usage of unmanned aerial vehicles (UAV) has increased in recent years and new application scenarios have emerged. Some of them involve tasks that require a high degree of autonomy, leading to increasingly complex systems. In order for a robot to be autonomous, it requires appropriate perception sensors that interpret the environment and enable the correct execution of the main task of mobile robotics: navigation. In the case of UAVs, flying at low altitude greatly increases the probability of encountering obstacles, so they need a fast, simple, and robust method of collision avoidance. This work covers the problem of navigation in unknown scenarios by implementing a simple, yet robust, environment-reactive approach. The implementation is done with both CPU and GPU map representations to allow wider coverage of possible applications. This method searches for obstacles that cross a cylindrical safety volume, and selects an escape point from a spiral for avoiding the obstacle. The algorithm is able to successfully navigate in complex scenarios, using both a high and low-power computer, typically found aboard UAVs, relying only on a depth camera with a limited FOV and range. Depending on the configuration, the algorithm can process point clouds at nearly 40 Hz in Jetson Nano, while checking for threats at 10 kHz. Some preliminary tests were conducted with real-world scenarios, showing both the advantages and limitations of CPU and GPU-based methodologies.

scholarly journals IEEE Access Special Section Editorial: Real-Time Machine Learning Applications in Mobile Robotics

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 89694-89698
Author(s):  
Aysegul Ucar ◽  
Jessy W. Grizzle ◽  
Maani Ghaffari ◽  
Mattias Wahde ◽  
H. Levent Akin ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Mobile Robotics ◽  
Special Section ◽  
Time Machine ◽  
Machine Learning Applications
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