Automated grasp planning for robotic hands is a complex problem when compared with the ease with which human hands grasp objects. Research in robotic grasp synthesis attempts to find novel ways in which a stable grasp can be achieved reliably. In this work, we present a grasping methodology that achieves optimized force closure grasps on 3D irregular objects. 3D objects in the form of polygonal meshes are parameterized to 2D shapes in order to reduce the search space by constraining robotic hands finger tips to be in contact with the objects surface. We use a Particle Swarm Optimization (PSO) based framework to optimize an initial grasp. The scheme has been validated on test-case 3D objects represented with surface tessellation for a 5-fingered DLR robotic hand.

A description is given of a low-cost laser ranger suitable for robot applications. The region to be observed is illuminated by a sinusoidal intensity distribution generated by an optical projection system with a laser source. The deformation of the sine-wave pattern is detected by a phase-sensing method widely used in optical interferometry, and can be easily related to the shape and range information. Over a range determined by the depth of field of the camera at a given aperture and focal setting, high-resolution measurements can be made. Experimental results show that at a camera distance of about 1 m, the resolution and repeatability in locating a flat 25-mm/sup 2/ surface are of the order of 0.2 mm.>