Most mission planning algorithms solve multi-robot-multi-mission problems based on mixed integer linear programming. In these algorithms, the rewards (or costs) of missions for each robot are calculated according to purpose user. Then, (robot-mission) pair that has maximum minimum is found in table and allocated robot. However, it hard design reward minimizing total completion time because not ...

Depth Completion can produce a dense depth map from sparse input and provide more complete 3D description of the environment. Despite great progress made in completion, sparsity low density ground truth still make this problem challenging. In work, we propose DenseLiDAR, novel real-time pseudo-depth guided completion neural network. We exploit obtained simple morphological operations to guide n...