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This paper explores a novel approach to dexterous manipulation, aimed at levels of speed, precision, robustness, and simplicity suitable for practical deployment. The enabling technology is a Direct-drive Hand (DDHand) comprising two fingers, two DOFs each, that exhibit high speed and a light touch. The test application is the dexterous manipulation of three small and irregular parts, moving them to a grasp suitable for a subsequent assembly operation, regardless of initial presentation. We employed four primitive behaviors that use ground contact as a “third finger”, prior to or during the grasp process: pushing, pivoting, toppling, and squeeze- grasping. In our experiments, each part was presented from 30 to 90 times randomly positioned in each stable pose. Success rates varied from 83% to 100%. The time to manipulate and grasp was 6.32 seconds on average, varying from 2.07 to 16 seconds. In some cases, performance was robust, precise, and fast enough for practical applications, but in other cases, pose uncertainty required time-consuming vision and arm motions. The paper concludes with a discussion of further improvements required to make the primitives robust, eliminate uncertainty, and reduce this dependence on vision and arm motion. 

Localizing contacts and collisions is an important aspect of failure detection and recovery for robots and can aid perception and exploration of the environment. Contrary to state-of-the-art methods that rely on forces and torques measured on the robot, this paper proposes a kinematic method for proprioceptive contact localization on compliant robots using velocity measurements. The method is validated on two planar robots, the quadrupedal Minitaur and the two-fingered Direct Drive (DD) Hand which are compliant due to inherent transparency from direct drive actuation. Comparisons to other state-of-the-art proprioceptive methods are shown in simulation. Preliminary results on further extensions to complex geometry (through numerical methods) and spatial robots (with a particle filter) are discussed. 

Robots operating in unstructured environments must localize contact to detect and recover from failure. For example, Fig. 1 shows a Minitaur robot that must localize where it has unexpectedly contacted the stair’s edge so that it can properly step over it. We propose a kinematic method for proprioceptive contact localization using velocity measurements. The method is validated on two planar robots, the quadrupedal Minitaur and the DD Hand gripper, and compared to other state of the art proprioceptive methods. We further show that the method can be extended to spatial robots by fusing the candidate contact points over time with a particle filter. 

The Direct Drive Hand (DDHand) project is exploring an alternative design philosophy for grippers. The conventional approach is to prioritize clamping force, leading to high gear ratios, slow motion, and poor transmission of force/motion signals. Instead, the DDHand prioritizes transparency: we view the gripper as a signal transmission channel, and seek high-bandwidth, highfidelity transmission of force and motion signals in both directions. The resulting design has no gears and no springs, occupying a new quadrant in the servo gripper design space. This paper presents the direct drive gripper design philosophy, compares the performance of different design choices, describes our current design and implementation, and demonstrates a fly-by “smack and snatch” grasping motion to show the gripper’s ability to safely detect and respond quickly to variations in the task environment.