LEAP Hand: Low-Cost, Efficient, and Anthropomorphic Hand for Robot
  Learning
Dexterous manipulation has been a long-standing challenge in robotics. While
machine learning techniques have shown some promise, results have largely been
currently limited to simulation. This can be mostly attributed to the lack of
suitable hardware. In this paper, we present LEAP Hand, a low-cost dexterous
and anthropomorphic hand for machine learning research. In contrast to previous
hands, LEAP Hand has a novel kinematic structure that allows maximal dexterity
regardless of finger pose. LEAP Hand is low-cost and can be assembled in 4
hours at a cost of 2000 USD from readily available parts. It is capable of
consistently exerting large torques over long durations of time. We show that
LEAP Hand can be used to perform several manipulation tasks in the real world
-- from visual teleoperation to learning from passive video data and sim2real.
LEAP Hand significantly outperforms its closest competitor Allegro Hand in all
our experiments while being 1/8th of the cost. We release detailed assembly
instructions, the Sim2Real pipeline and a development platform with useful APIs
on our website at https://leap-hand.github.io/
6501349b1e14749e840f9250
Kenneth Shaw
6501349b1e14749e840f9251
Ananye Agarwal
6501349b1e14749e840f9252
Deepak Pathak
admin_assigned
2023-09-14T08:27:18.937Z
648098bac0d3c70316d21346
/avatars/e4bf018c85730eda57f43e66c3deaeef.svg
Deepak pathak
user
dpkpathak
LEAP Hand: Low-Cost, Efficient, and Anthropomorphic Hand for Robot
  Learning
Dexterous manipulation has been a long-standing challenge in robotics. While
machine learning techniques have shown some promise, results have largely been
currently limited to simulation. This can be mostly attributed to the lack of
suitable hardware. In this paper, we present LEAP Hand, a low-cost dexterous
and anthropomorphic hand for machine learning research. In contrast to previous
hands, LEAP Hand has a novel kinematic structure that allows maximal dexterity
regardless of finger pose. LEAP Hand is low-cost and can be assembled in 4
hours at a cost of 2000 USD from readily available parts. It is capable of
consistently exerting large torques over long durations of time. We show that
LEAP Hand can be used to perform several manipulation tasks in the real world
-- from visual teleoperation to learning from passive video data and sim2real.
LEAP Hand significantly outperforms its closest competitor Allegro Hand in all
our experiments while being 1/8th of the cost. We release detailed assembly
instructions, the Sim2Real pipeline and a development platform with useful APIs
on our website at https://leap-hand.github.io/
LEAP Hand, a low-cost anthropomorphic robotic hand, outperforms more expensive alternatives in real-world manipulation tasks including visual teleoperation and learning from video data.