Automated Driving

Simultaneous Contact, Gait, and Motion Planning for Robust Multilegged Locomotion via Mixed‑Integer Convex Optimization

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TRI Author: Hongkai Dai

All Authors: Bernardo Aceituno-Cabezas, Carlos Mastalli, Hongkai Dai, Michele Focchi, Andreea Radulescu, Darwin G. Caldwell, Jose Cappelletto, Juan C. Grieco, Gerardo Fernandez-Lopez, Claudio Semini

Traditional motion planning approaches for multilegged locomotion divide the problem into several stages, such as contact search and trajectory generation. However, reasoning about contacts and motions simultaneously is crucial for the generation of complex whole-body behaviors. Currently, coupling theses problems has required either the assumption of a fixed gait sequence and flat terrain condition, or nonconvex optimization with intractable computation time. In this letter, we propose a mixed-integer convex formulation to plan simultaneously contact locations, gait transitions, and motion, in a computationally efficient fashion. In contrast to previous works, our approach is not limited to flat terrain nor to a prespecified gait sequence. Instead, we incorporate the friction cone stability margin, approximate the robot's torque limits, and plan the gait using mixed-integer convex constraints. We experimentally validated our approach on the HyQ robot by traversing different challenging terrains, where nonconvexity and flat terrain assumptions might lead to suboptimal or unstable plans. Our method increases the motion robustness while keeping a low computation time. Read More

Citation: Aceituno-Cabezas, Bernardo, Carlos Mastalli, Hongkai Dai, Michele Focchi, Andreea Radulescu, Darwin G. Caldwell, José Cappelletto, Juan C. Grieco, Gerardo Fernández-López, and Claudio Semini. "Simultaneous contact, gait, and motion planning for robust multilegged locomotion via mixed-integer convex optimization." IEEE Robotics and Automation Letters 3, no. 3 (2017): 2531-2538.