A method for adjusting one or more calibration parameters of a plurality of sensors (140, 150) of different types, comprising: capturing, by a plurality of sensors (140, 150) associated with a vehicle, a set of point cloud data indicative of at least one surrounding object as the vehicle travels along a trajectory; determining, by a processor, a coplanarity associated with the set of point cloud data based on a difference of normal vectors of each of points in a plurality of scales associated with the set of point cloud data, wherein the coplanarity is a degree that two or more points in the set of point cloud data are within a same plane, and each of the plurality of scales is defined by two points in the set of point cloud data; filtering, by the processor, the set of point cloud data based on the coplanarity associated with the set of point cloud data; and adjusting, by the processor, at least one calibration parameter of the plurality of sensors (140, 150) based on the filtered set of point cloud data, wherein the filtering, by the processor, the set of point cloud data based on the coplanarity associated with the set of point cloud data includes: calculating a first normal vector associated with a point in a point cloud represented by the set of point cloud data in a first scale; calculating a second normal vector associated with the point in a second scale, the second scale being smaller than the first scale; calculating a difference of the first normal vector and the second normal vector; and removing the point from the point cloud based on the difference being greater than a threshold. capturing, by a plurality of sensors (140, 150) associated with a vehicle, a set of point cloud data indicative of at least one surrounding object as the vehicle travels along a trajectory; determining, by a processor, a coplanarity associated with the set of point cloud data based on a difference of normal vectors of each of points in a plurality of scales associated with the set of point cloud data, wherein the coplanarity is a degree that two or more points in the set of point cloud data are within a same plane, and each of the plurality of scales is defined by two points in the set of point cloud data; filtering, by the processor, the set of point cloud data based on the coplanarity associated with the set of point cloud data; and adjusting, by the processor, at least one calibration parameter of the plurality of sensors (140, 150) based on the filtered set of point cloud data, wherein the filtering, by the processor, the set of point cloud data based on the coplanarity associated with the set of point cloud data includes: calculating a first normal vector associated with a point in a point cloud represented by the set of point cloud data in a first scale; calculating a second normal vector associated with the point in a second scale, the second scale being smaller than the first scale; calculating a difference of the first normal vector and the second normal vector; and removing the point from the point cloud based on the difference being greater than a threshold. calculating a first normal vector associated with a point in a point cloud represented by the set of point cloud data in a first scale; calculating a second normal vector associated with the point in a second scale, the second scale being smaller than the first scale; calculating a difference of the first normal vector and the second normal vector; and removing the point from the point cloud based on the difference being greater than a threshold.