Fig. 5: Human-like diverse grasping strategies for single objects.
From: Embedding high-resolution touch across robotic hands enables adaptive human-like grasping
a, A total of 23 objects, varying in dimensions and geometrical complexity, are chosen to assess the efficacy of the grasp generation method. b–d, The landscape of possible grasps is depicted as a disconnectivity graph, generated using the ADELM algorithm. e, For the pliers, the diversity in grasp strategies mirrors its common usage in daily human activities. f, This diversity in grasping strategies is maintained even when the object possesses complex geometric features. g, Comprehensive categorization of the generated grasps for all 23 objects, on the basis of human grasp types adopted from ref. 24. The results collectively cover all 19 common grasp types, implying the human-like diversity of the generated grasping strategies.
