We participated in the "Tsukuba Challenge 2022" Main Race held on Sunday, November 20, 2022.
Since FY2021, we have been developing "PANDA," an outdoor driving robot.
The hardware design has been significantly modified to address stability and sensor placement issues discovered through experiments with "Rafute."
The center of gravity was lowered so the robot could travel stably on uneven terrain.
The design is divided into two modules for the bogie and sensor sections, allowing easy modification of sensor types and placement.
We are currently using "PANDA" to compare the types and placement of sensors and SLAM algorithms that are effective for outdoor driving.
We are also developing a high-precision position estimation function by combining 3D point clouds, IMU, and RTK-GNSS, using the high-precision positioning service "ichimill" for RTK-GNSS positioning.
Unfortunately, we had to retire due to issues with the robot. We were able to implement both self-localization systems using LiDAR and GNSS independently, but we were unable to integrate these two systems. Therefore, we relied solely on LiDAR for the main race. However, an unexpected bug occurred at the starting point due to insufficient practice time, preventing us from beginning the operation and having to retire as a result.
We plan to participate in the "Tsukuba Challenge" again in 2023. Your continued support is greatly appreciated.
Tsukuba Challenge 2022 Homepage - final
*Japanese only