AutoCart Final Report
Auto-Cart-Final-Report
5/2/20 Zehong Progress Report
This week I’ve mainly been working on figuring out the most efficient and effective way to present our pathfinding algorithm. I have experimenting with the best method to record my portion of the final presentation video. Ideally, slides would help as a visual guide and I would be voicing over to help explain the diagrams. Finally, I have also been working on the final report. This will also be the majority of work left for the following week.
4/26 Team Update
Zeyi worked on integration this week and improving the user interface. He changed the map to have multiple items on a single node to help the product become more robust. He also changed the node list and item list to display the remaining nodes and items on the planed route. Overall, he has more descriptive changes on his personal update. Zehong further improved his algorithm and further integrated with Zeyi’s user interface. There were some bugs when integrating, and Zehong…
4/25 Zehong Progress Report
This week I majorly worked in integrating my path planning algorithm with Zeyi’s user interface. In the process, we identified some bugs with the algorithm and I fixed them. First bug was with the replan() function. I ended up referencing some local variable that only existed in my version of the path planning algorithm (duplicate variable names in testing code). This created a problem on Zeyi’s side where replan() only works for certain pairs of nodes. It was a rather…
4/19 Team Update
This week, integration was the main theme for our group. We also had some individual tasks we had to do to help smoothen the integration. Carlo’s focused on integrating the range sensor code with Zeyi and Zehong’s work. He also focused on altering the design to improve the feasibility of the sensors. Finally, he has been preparing for the demo and methods to present the sensors in the presentation. To get a more detailed description, please read his weekly update….
4/19 Zehong Progress Report
This week, I first addressed the problem with local re-planning. I was thinking if an obstacle were to appear in the optimal route between Node1 and Node2, I can simple recall the saved shortest path between Node1 and Node2 that has been pre-planned to “go around” the obstacle. But I soon realized that due to the way my algorithm is set up, every pair of adjacent nodes in the optimal route are neighbors. This leads to a problem that if…
4/12 Team Update
Zehong mainly worked on updating the algorithm further to add additional details. The algorithm now can start and end at different nodes. This helps decrease the limitations of the algorithm. In addition, Zehong focused on generating maps this week to help showcase exactly what is going on. He then ran multiple tests to make sure he is accounting for all possible scenarios. For more detailed descriptions, please read his update. Zeyi continued on improving the user interface and the additional…
4/12 Zehong Lin status report
After talking with professor during the last meeting, I first updated the algorithm so that it can start and end of different nodes. I then embarked on testing the limits of my algorithm. To do that, I first need to generate maps of my own. I first randomly generate the x and y coordinates of n nodes. The weight(distance) of edge between each pair of nodes is always the euclidean distance. I chose this to be the distance to avoid problems…
4/5 Team Progress week 8
This week, during our meetings, we have discussed and planned for methods of integration for week 9 and 10. Everyone in the team has made substantial progress in their individual components. Zeyi has finished the majority of basic functions of the User Interface for our website. The intergration portion would be intergrating to Zehong’s algorithm to calculate the most optimal path and planned path given by the algorithm. A more detailed description of Zeyi’s progress is in his weekly report….
4/5 Zehong’s Progress Report
This week, I finished implementing the entire path planning algorithm. It takes in two inputs, an origin and a list of nodes the cart needs to visit; and it returns the optimal route. As promised, the algorithm pre-computes the shortest distance between each path of nodes in the map using A* with the heuristic function being the euclidean distance between the two nodes. The shortest paths between each path of nodes are stored in data structure to be used in…