@inproceedings{manuelli_localizing_2016,
	title = {Localizing external contact using proprioceptive sensors: {The} {Contact} {Particle} {Filter}},
	shorttitle = {Localizing external contact using proprioceptive sensors},
	doi = {10.1109/IROS.2016.7759743},
	abstract = {In order for robots to interact safely and intelligently with their environment they must be able to reliably estimate and localize external contacts. This paper introduces CPF, the Contact Particle Filter, which is a general algorithm for detecting and localizing external contacts on rigid body robots without the need for external sensing. CPF finds external contact points that best explain the observed external joint torque, and returns sensible estimates even when the external torque measurement is corrupted with noise. We demonstrate the capability of the CPF to track multiple external contacts on a simulated Atlas robot, and compare our work to existing approaches.},
	booktitle = {2016 {IEEE}/{RSJ} {International} {Conference} on {Intelligent} {Robots} and {Systems} ({IROS})},
	author = {Manuelli, L. and Tedrake, R.},
	month = oct,
	year = {2016},
	keywords = {Atlas robot, CPF, Collision avoidance, Legged locomotion, Observers, Robot sensing systems, Torque, contact particle filter, external contact localization, external joint torque, external sensing, external torque measurement, humanoid robots, legged locomotion, particle filtering (numerical methods), proprioceptive sensors, rigid body robots},
	pages = {5062--5069}
}

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