In order to make the humanoid robot walk freely in complicated circumstance,the reliable capabilities for obtaining plane information from its surroundings are demanded.A system for extracting planes from data taken by stereo vision was presented.After the depth image was obtained,the pixels of each line were scanned and split into straight line segments.The neighbouring relation of line segments was kept in link structure.The groups of three line segments were selected as seed regions.A queue was maintained for storing seed regions,and then the plane region was expanded around the seed region.The process of region growing continued until the queue of seed regions was empty.After trimming,the edges of the planes became smooth.In the end,extracted planes were obtained.In the experiment,two models were used:pipe and stairs.Two planes in pipe model and six planes in stairs model were extracted exactly.The speed and precision of algorithm can satisfy the demands of humanoid robot's navigation.
In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for the humanoid. In the second part, the compound biped locomotion algorithm is presented based on the reference motion and reference Zero Moment Point (ZMP). This novel algorithm includes calculation of the upper body motion and trajectory of the Center of Gravity (CoG) of the robot. First, disturbances from the environment are eliminated by the compensational movement of the upper body; then based on the error between a reference ZMP and the real ZMP as well as the relation between ZMP and CoG, the CoG error is calculated, thus leading to the CoG trajectory. Then, the motion of the robot converges to its reference motion, generating stable biped walking. Because the calculation of upper body motion and tra-jectory of CoG both depend on the reference motion, they can work in parallel, thus providing double insurances against the robot's collapse. Finally, the algorithm is validated by different kinds of simulation experiments.
