While complex hands seem to offer generality, simple hands are often more practical. This raises the question: how do generality and simplicity trade off in the design of robot hands? This paper explores the tension between simplicity in hand design and generality in hand function. It raises arguments both for and against simple hands, it considers several familiar examples, and it proposes an approach for autonomous manipulation using a general-purpose but simple hand. We explore the approach in the context of a bin-picking task, focused on grasping, recognition, and localization. The central idea is to use learned knowledge of stable grasp poses as a cue for object recognition and localization. This leads to some novel design criteria, such as minimizing the number of stable grasp poses. Finally, we describe experiments with two prototype hands to perform bin-picking of highlighter markers.

Tactile sensing provides critical information, such as force, texture, shape or temperature, in manipulation tasks. In particular, tactile sensors traditionally used in robotics are emphasized in contact force determination for grasping control and object recognition. Nevertheless, slip detection is also crucial to successfully manipulate an object. Several approaches have appeared to detect slipping, the majority being a combination of complex sensors with complex algorithms. In this paper, we deal with simplicity, analyzing how a novel, but simple, algorithm, based on micro-vibration detection, can be used in a simple, but low-cost and durable, force sensor. We also analyze the results of using the same principle to detect slipping in other force sensors based on flexible parts. In particular, we show and compare the slip detection with: (i) a flexible finger, designed by the authors, acting as a force sensor; (ii) the finger torque sensor of a commercial robotic hand; (iii) a commercial six-axis force sensor mounted on the wrist of a robot; and (iv) a fingertip piezoresistive matrix sensor.