Ground vehicle approaching negative obstacles

ROS pointcloud and odometry streams recorded during various scenarios where a robotic ground vehicle approaches negative obstacles. These values were generated by the Wildcat SLAM software based on measurements by a Velodyne lidar and an IMU. ROS topics include: * heightmap_cloud: heightmap represented as a pointcloud * heightmap_to_costmap/costmap: costmap represented as a pointcloud (each z value has been reduced by 0.1 to make visualising the path easier) * ohm: occupancy voxel grid represented as a pointcloud * slam/odom/high/cloud: pointcloud generated by Wildcat * tf: frames used for visualisation, odom is considered fixed Often negative obstacles cannot be observed directly by a ground vehicle as they are obscured by the upper surface between the vehicle and the obstacle. This data contains examples that can be used to demonstrate methods of indirectly inferring negative obstacles from typical observations made during an approach.