A simplistic solution to the 8 puzzle game using Brute Force Algorithm is developed. Its time-complexity is high due to the fact that there is no cost function but this makes it easy to lay foundations to graph theory. Manhattan distance as a cost function is aimed to be applied to make it time efficient.
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Utilized a swarm of 6 rovers to explore a bounded region and collect maximum arbitrary placed targets.Experimented with multiple space exploration strategies such as spiral, lawnmower motions, Hilbert curves etc. Designed and generated a custom map object that populates incrementally with rover movement. Also, implemented an optimized collision avoidance algorithm for rovers using ROS, C++ and Gazebo.
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Dijkstra and A* algorithms were implemented on a point and a rigid robot on a given map to find the optimal path. Simulated on TurtleBot2 with non-holonomic constraints. The simulation is then performed on the map of the Robot Realization Lab of University of Maryland.
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Inverse kinematics was calculated for Baxter Robot for pick and place application along with obstacle avoidance. The simulation was carried out in the V-Rep.
Implemented A* and Weighted A* algorithms
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Implemented Dijkstra algorithm
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Implemented BFS algorithm
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