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Perceptive Model Predictive Control for Continuous Mobile Manipulation

This video is supplementary material to the work "Perceptive Model Predictive Control for Continuous Mobile Manipulation" published in RA-L 2020. J. Pankert and M. Hutter, “Perceptive Model Predictive Control for Continuous Mobile Manipulation,” IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 6177–6184, Oct. 2020, doi: 10.1109/LRA.2020.3010721. IEEE paper link: https://ieeexplore.ieee.org/abstract/... Open Access Version: https://www.research-collection.ethz.... Paper Abstract: A mobile robot needs to be aware of its environment to interact with it safely. We propose a receding horizon control scheme for mobile manipulators that tracks task space reference trajectories. It uses visual information to avoid obstacles and haptic sensing to control interaction forces. Additional constraints for mechanical stability and joint limits are met. The proposed method is faster than state of the art sampling based planners, open-source available and can be implemented on a broad class of robots. We validate the method both in simulation and through extensive hardware experiments with a multitude of mobile manipulation platforms. The resulting software package is released with this paper. Force Torque Sensor used: https://www.botasys.com/rokubi