Fig. 2: Knowledge-driven model of the robot and its numerical simulation.
From: Machine learning-based framework for wall-perching prediction of flying robot
a Discrete model based on FEM, which is used to solve the contact-impact problem during the landing event. b Displacement of the spine under three sets of initial landing conditions with lift strengthening (I indicates θ0=−5° and v0=0.4 m/s; II indicates θ0=−5° and v0=0.8 m/s; III indicates θ0=−10° and v0=0.8 m/s). The solid and short dash lines are the displacements in the x and z direction, respectively. The symbol star represents the occurrence of collision between the spine and wall. c The lift curves during the landing event for receding cases. d The lift curves during the landing event for strengthening cases. e The resultant velocity of the spine during the landing process for 4 typical landing behaviors. The success and failure envelop regions (i.e., the green and red areas) that we summarized for the landing events under 114 sets of initial landing conditions are also shown. The three values in legend in this figure are pitch of flying robot θ0,initial horizontal incidence velocity v0 and lift FL, respectively (where LR means lift receding and LS means lift strengthening). f The robot undergoes a fixed-axis rotation where the rotation center is the contact point of the tail during the “perfect landing” process. g The robot body flips upward using the wheels as the rotation center during the “perfect landing” process. h The wheel separates from the wall and then contacts it again during the “normal landing” process. i The maximum von-Mises stress appears at the root of the landing rod when the robot contacts the wall. j The maximum von-Mises stress appears in the connecting piece. If the high velocity causes excessive stress, the structure will be damaged. k Configuration of robot when it is in the success perching state on the wall.
