A method for adjusting one or more calibration parameters of a plurality of sensors of different types, comprising: capturing, by a plurality of sensors 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 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 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 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 . <EOS>