Dynamic Capturing Strategy for a 2-D Stick-Shaped Object Based on Friction Independent Collision

The contact problem in Lagrangian systems with redundant frictional bilateral and unilateral constraints and singular mass matrix. The all-sticking contacts problem

“…If we deal with 3D friction, d = 3 and λ st t,u has dimension 2m u = 2m. In case of planar friction d = 2 and it has dimension m u = m. The problem in (34) is an MLCP with unknowns λ st n,u and λ st t,u . There are various ways to analyse MLCPs [26].…”

“…Force and form closure, as well as various stability notions and criteria are proposed in [47,22,16,9,48,49,62,68,52,53,33,10,34,51] for object grasping and biped robots. Static equilibrium problems are anaylsed and algorithms are presented [51,52,33,68,49,16,48,9], dynamical effects are taken into account in [47,62,34]. Most of these works rely on the careful study of contact and external wrenches, and yield precise criteria on wrenches and contact points arrangements so that stability or static equilibrium are guaranteed [10,48,49].…”

Grasping strategy for moving object using Net-Structure Proximity Sensor and vision sensor

“…In this paper, a grasping strategy for a moving object as shown in Fig.1 is proposed. This strategy integrates feed-forward control along the trajectory of the object predicted from vision information The authors are with Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Tokyo, Japan suzuki@mce.uec.ac.jp, koyama@rm.mce.uec.ac.jp, ming@mce.uec.ac.jp, shimojo@mce.uec.ac.jp In general, in the task of grasping a moving object by a robot-hand-arm system, the trajectory of the object is predicted based on time-series position data from stereocamera systems, RGBD sensors, and other vision sensors, and then, the time to grasp and the target position and posture of the robot-hand-arm are determined [4], [5], [6], [7], [8]. Hove et al proposed a method for catching a thrown ball by real-time estimation of the trajectory and manipulator control [4].…”

“…Imai et al realized dynamic active catching of a falling ball and cylinder with the high-speed and precise hand system [6]. Higashimori et al dealt with dynamic active catching of a stick-shaped object with large rotational velocity [7]. Bäuml et al achieved highly reliable ball catching using real-time motion planning based on the trajectory prediction visual tracking and Extended Kalman Filter [8].…”

Dynamic modeling of robotic fish and its experimental validation

“…Along with the advancement of technology in both sensing and actuation, dynamic skills in robotics have been developed [1], [2]. In the present, however, it is difficult for multifingered robot hands to exceed human's capability from the viewpoint of dexterity.…”