Hassan Zargarzadeh

Sadra Naddaf-Sh, M-Mahdi Naddaf-Sh, Amir R. Kashani et al.

Pavement condition evaluation is essential to time the preventative or rehabilitative actions and control distress propagation. Failing to conduct timely evaluations can lead to severe structural and financial loss of the infrastructure and complete reconstructions. Automated computer-aided surveying measures can provide a database of road damage patterns and their locations. This database can be utilized for timely road repairs to gain the minimum cost of maintenance and the asphalt's maximum durability. This paper introduces a deep learning-based surveying scheme to analyze the image-based distress data in real-time. A database consisting of a diverse population of crack distress types such as longitudinal, transverse, and alligator cracks, photographed using mobile-device is used. Then, a family of efficient and scalable models that are tuned for pavement crack detection is trained, and various augmentation policies are explored. Proposed models, resulted in F1-scores, ranging from 52% to 56%, and average inference time from 178-10 images per second. Finally, the performance of the object detectors are examined, and error analysis is reported against various images. The source code is available at https://github.com/mahdi65/roadDamageDetection2020.

Mehdi Dadvar, Saeed Moazami, Harley R. Myler et al.

The hunter and gatherer approach copes with the problem of dynamic multi-robot task allocation, where tasks are unknowingly distributed over an environment. This approach employs two complementary teams of agents: one agile in exploring (hunters) and another dexterous in completing (gatherers) the tasks. Although this approach has been studied from the task planning point of view in our previous works, the multi-robot exploration and coordination aspects of the problem remain uninvestigated. This paper proposes a multi-robot exploration algorithm for hunters based on innovative notions of "expected information gain" to minimize the collective cost of task accomplishments in a distributed manner. Besides, we present a coordination solution between hunters and gatherers by integrating the novel notion of profit margins into the concept of expected information gain. Statistical analysis of extensive simulation results confirms the efficacy of the proposed algorithms compared in different environments with varying levels of obstacles complexities. We also demonstrate that the lack of effective coordination between hunters and gatherers significantly hurts the total effectiveness of the planning, especially in environments containing dense obstacles and confined corridors. Finally, it is statistically proven that the overall workload is distributed equally for each type of agent which ensures that the proposed solution is not biased to a particular agent and all agents behave analogously under similar characteristics.

Saeed Moazami, M-Mahdi Naddaf-Sh, Srinivas Palanki et al.

This paper discusses the design, modeling, and control of Norma, a novel 2 DOF mobile spherical robot (SR). The propelling mechanism of this robot consists of two actuators: a slider, and a rotational pendulum located on the SR's diagonal shaft. The slider can translate along the shaft and shift the robot's center of gravity towards the robot's sides. The pendulum rotates around the shaft to propel the SR to roll forward and backward. These two actuators enable the SR to perform both rolling and turning maneuvers as a nonholonomic robot. The advantage of the proposed mechanical design lies in its convenience of physical implementation, agility, and accurate mathematical model. The Euler Lagrange approach is utilized to derive the dynamics of the proposed mechanical structure using minimum simplifications possible. Further, a path tracking control scheme is introduced for a smooth trajectory. Finally, simulations are carried out in MATLAB to verify the accuracy of the mathematical model and the effectiveness of the controller against experimental results.