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We present VILENS (Visual Inertial Lidar Legged Navigation System), anodometry system for legged robots based on factor graphs. The key novelty isthe tight fusion of four different sensor modalities to achieve reliableoperation when the individual sensors would otherwise produce degenerateestimation. To minimize leg odometry drift, we extend the robot's state with alinear velocity bias term which is estimated online. This bias is observablebecause of the tight fusion of this preintegrated velocity factor with vision,lidar, and IMU factors. Extensive experimental validation on different ANYmalquadruped robots is presented, for a total duration of 2 h and 1.8 km traveled.The experiments involved dynamic locomotion over loose rocks, slopes, and mudwhich caused challenges like slippage and terrain deformation. Perceptualchallenges included dark and dusty underground caverns, and open andfeature-deprived areas. We show an average improvement of 62% translational and51% rotational errors compared to a state-of-the-art loosely coupled approach.To demonstrate its robustness, VILENS was also integrated with a perceptivecontroller and a local path planner.

VILENS: Visual, Inertial, Lidar, and Leg Odometry for All-Terrain Legged Robots