ThreeDimensional Truss Modelling for Biped Climbing Robots Recognizing and modelling the threedimensional (3D) trussstyle environment, consisting of cylinder members, is a challenging task for climbing robots. Stateoftheart segmentation algorithms always suffer from incomplete membersegmentation. To solve this problem, in this paper we propose a truss environment modelling (TEM) method using a sliding bounding box algorithm. TEM can obtain accurate poses of the members in truss environments by two strategies. First, the remaining incomplete segmented members are localized by a sliding bounding box along the axis of the members. After that, members are merged based on the new endpoints detected after projecting points in the new bounding box onto the axis, reducing the uncertainty and complexity of members merging. Our proposed method was verified by experiments with steady performance, which satisfied the requirements of the climbing robots.

Representation of 3D Structure for Path Planning with Biped WallClimbing Robots For biped wallclimbing robots, mapping and extraction of the parametric expression map denote challenging tasks, especially for the environments where lidar measurements degrade. To build a representation of the environment for global path planning, a threedimensional (3D) planar structure modelling and parameterization system is proposed. The system includes the two following tasks: 1) mapping by a lidarIMU fusion method in which point cloud registration algorithm tracks the lidar poses with the initial transformation matrix provided by IMU integration; 2) extracting the vertexes of planes that represent the parametric expression of the 3D planar structure. Experiments showed that our mapping algorithm was more rubust than others in the lidardegraded environment. Besides, the precision analysis verified that the parametric expression map was accurate enough to be used for path planning of biped wallclimbing robots.