Abstract

The core technology of the Big Dog quadruped robot is analyzed. Adapting to the rough terrain is the main design clues of the Big Dog. Improving horizontal and vertical degrees of freedom linkage ability is the main innovation of structure design. Not good motion characteristics, such as robot's center of gravity ups and downs and self disturbance are the main reasons for being difficult to control. The components and advantage of the hydraulic power system are analyzed. Solving the driver problem of legged vehicles is the fundamental goal of the hydraulic system development. Supporting leg slipping or not, pitch and roll angle of the body too large or not are the main parameters as monitoring robot's movement condition. IMU and joint encoder can detect the state parameters of the body and limbs. Terrain of foot placement can be restored by pressure sensor. Three-in-one can build a virtual model. By the virtual model, robot's center of gravity and other key control process parameters can be calculated. At the same time, locomotion control system can do action drill roughly and accurate planning of kinematics or dynamics. The deviation of planning and prototype model is taken as the feedback for closed-loop control. LS3 constructs the navigation system of three-dimensional laser scanner and binocular vision as the main. LS3 can stride across rocky terrain by visual terrain reconstruction. Software system can integrate all the basic functions as an organic whole. Autonomy and intelligence of robot are discussed. Big Dog/LS3 and Curiosity Mars Rover are compared and analyzed. Big Dog has three big problems currently: instantaneously unable to increase hydraulic value significantly, all kinds of damage in mechanical transmission, bionic design not thoroughness. For the inadequacies of Big Dog, several improvements are analyzed on the LS3. Petman, Cheetah and Wildcat robot are briefly analyzed. Atlas biped robot has crash protection function and can recovery equilibrium status quickly after external force hitting by virtual model.

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