cs.ROSep 27, 2026

Multi-Terrain Mastery: A Comprehensive Controller for Bipedal Locomotion

Authors: Oluwami Dosunmu-Ogunbi, Aayushi Shrivastava

Organizations: Mechanical Engineering Department Ohio Northern University Ada, United States of America · Mechanical Engineering Department University of California, Berkeley Berkeley, United States of America

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Abstract

Advancing bipedal robots to navigate diverse terrains remains a significant challenge in robotics. Traditional locomotion controllers excel on specific surfaces but struggle across varied environments, limiting their practical applications. Given the unpredictable nature of real-world environments, a single controller capable of handling multiple terrains is ideal, eliminating the need for multiple specialized controllers. We propose a multi-terrain controller to enhance the versatility and robustness of bipedal locomotion. Building on previous work with a stance ankle motor for stability on inclined and rough surfaces, this paper extends capabilities to steep wet uneven grassy slopes, and compliant terrains such as sand, gravel, rocks, and constrained terrains like staircases. To address the unique demands of these terrains, we introduce a new impact map that is essential for maintaining performance and robustness against unseen terrains. We also discuss in detail the control structure for real-time deployment on the robot. We validate our controller on the 20 degree-of-freedom Cassie bipedal robot.

Figures & tables

Figure 1: A collage of screenshots where the Cassie bipedal robot walks on grassy slope, sand, rocks, moving walkway, inclined treadmill and stairs.
Figure 2: Schematic diagram of the multi-terrain locomotion controller.
Figure 3: Schematic of an inverted pendulum used to derive a variation of the ALIP model.
Figure 4: Schematic depicting geometry variables for computing impact map based off of a lineariziation of a nominal trajectory.
Figure 5: A series of images depicting hardware results of Cassie bipedal robot walking through the Robot Playground, where the robot walked continuously through sand, gravel, and rocks. The original video can be found in [ 17 ]
Figure 6: A series of images depicting hardware results of Cassie bipedal robot walking on grassy slope with an estimated average gradient of approximately 22 degrees from a side view perspective. The original video can be found in [ 18 ]
Figure 7: A series of images depicting hardware results of Cassie bipedal robot walking on shallow stairs from a back view perspective. Each step is 2.5 inches in height, with a depth of 12 inches. The original video can be found in [ 20 ]

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