TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot
  Learning
Exploiting the promise of recent advances in imitation learning for mobile
manipulation will require the collection of large numbers of human-guided
demonstrations. This paper proposes an open-source design for an inexpensive,
robust, and flexible mobile manipulator that can support arbitrary arms,
enabling a wide range of real-world household mobile manipulation tasks.
Crucially, our design uses powered casters to enable the mobile base to be
fully holonomic, able to control all planar degrees of freedom independently
and simultaneously. This feature makes the base more maneuverable and
simplifies many mobile manipulation tasks, eliminating the kinematic
constraints that create complex and time-consuming motions in nonholonomic
bases. We equip our robot with an intuitive mobile phone teleoperation
interface to enable easy data acquisition for imitation learning. In our
experiments, we use this interface to collect data and show that the resulting
learned policies can successfully perform a variety of common household mobile
manipulation tasks.
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Jimmy Wu
claimed_verified
2024-12-17T10:34:45.672Z
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/avatars/78e175e131fe472257c2f93787e463a1.svg
Jimmy Wu
user
jimmyyhwu
67614ef841245764e08a2813
William Chong
67614ef841245764e08a2814
Robert Holmberg
67614ef841245764e08a2815
Aaditya Prasad
67614ef841245764e08a2816
Yihuai Gao
67614ef841245764e08a2817
Oussama Khatib
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Shuran Song
67614ef841245764e08a2819
Szymon Rusinkiewicz
67614ef841245764e08a281a
Jeannette Bohg
claimed_verified
2024-12-18T09:52:57.542Z
676272a59865895e253ceee5
https://cdn-avatars.huggingface.co/v1/production/uploads/676272a59865895e253ceee5/Nz51Y-G49SD19lQEjH6Yd.jpeg
Jeannette Bohg
user
jbohg
TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot
  Learning
Exploiting the promise of recent advances in imitation learning for mobile
manipulation will require the collection of large numbers of human-guided
demonstrations. This paper proposes an open-source design for an inexpensive,
robust, and flexible mobile manipulator that can support arbitrary arms,
enabling a wide range of real-world household mobile manipulation tasks.
Crucially, our design uses powered casters to enable the mobile base to be
fully holonomic, able to control all planar degrees of freedom independently
and simultaneously. This feature makes the base more maneuverable and
simplifies many mobile manipulation tasks, eliminating the kinematic
constraints that create complex and time-consuming motions in nonholonomic
bases. We equip our robot with an intuitive mobile phone teleoperation
interface to enable easy data acquisition for imitation learning. In our
experiments, we use this interface to collect data and show that the resulting
learned policies can successfully perform a variety of common household mobile
manipulation tasks.
A design for an inexpensive, holonomic mobile manipulator with powered casters enables easy data collection via teleoperation for imitation learning in household tasks.
imitation learning mobile manipulator powered casters holonomic teleoperation interface