Design and implementation of MARS Rover
Author: Dr. Mohammad Harun Or Rashid, Hasib Md Abid Bin Farid, G. M. Shahariar, Md Robin Sheikh and others.
Abstruct: The AUST Mars Rover, developed for the 2023 University Rover Challenge, exemplifies an integrated robotic platform engineered to execute autonomous navigation, scientific analysis, and remote manipulation in Mars-analog environments. The mechanical architecture features a stainless-steel octagonal chassis with a counter-rotating differential system and custom multi-material wheels, enhancing stability on uneven surfaces. A six-degree-of-freedom aluminum robotic arm, equipped with a rotational two-jaw 3D-printed gripper, facilitates precise handling of diverse sample types. The electrical system incorporates a multi-voltage Li-Po–based power distribution network, custom PCB modules, high-capacity motor drivers, and redundant safety mechanisms, including current-sensor-triggered shutdown and a mechanical kill switch. Long-range communication with the ground station is achieved through a 5-GHz FCC-compliant link with UDP-based low-latency video streaming and GPS-assisted fail-safe recovery. The software subsystems encompass Java-based graphical interfaces, inverse-kinematics-driven arm control, sensor-integrated data logging, and autonomous navigation algorithms utilizing obstacle detection and OpenCV-based image processing. The rover’s scientific payload integrates environmental sensors (pH, gas, humidity, pressure, and NPK analysis) with an onboard wet-chemistry laboratory capable of conducting protein and lipid detection using Biuret and Sudan-III assays. Collectively, these systems enable in-situ assessment of geological and biochemical properties pertinent to astrobiological research. This multidisciplinary design illustrates a cohesive and operationally robust rover platform suitable for Mars-analog field missions and educational robotics research.
A comprehensive and comparative study of maze-solving techniques by implementing graph theory
Author: Adil MJ Sadik, Maruf A Dhali, Hasib Md Abid Bin Farid, Tafhim U Rashid, A Syeed
Abstract: Solving a 3-D square maze through an autonomous robot is gaining immense popularity among the robotics aspirants. IEEE has established a set of rule for this and launched a competition named “Micromouse” where an autonomous robot or mice solves an unknown maze. Without deploying Artificial Intelligence technique it’s not possible to do this task efficiently. Several algorithms which originate from graph theory (GT) and non graph theory (NGT) are currently being used to program the robot or mice. In this paper we have elucidated how graph theory can be used to solve mazes. With adequate investigation it is verified how graph theory dominates over non graph theory algorithms. The process of generating maze solving algorithm from graph theory is also explained. To compare the algorithms efficiency, they are simulated artificially and a comprehensive study is done by interpreting the statistics of interest. The simulation results lead us towards a conclusion about the nature, behavior and efficiency of these algorithms. Upon considering all the regulating factors which can alter the performance of an algorithm, some proposals have been drawn. It will be helpful to any micro mouse aspirant while choosing an algorithm to design the robot.