Robot Grasp Planning: A Learning from Demonstration-Based Approach.

ABSTRACT: Robot grasping constitutes an essential capability in fulfilling the complexities of advanced industrial operations. This field has been extensively investigated to address a range of practical applications. However, the generation of a stable grasp remains challenging, principally due to the constraints imposed by object geometries and the diverse objectives of the tasks. In this work, we propose a novel learning from demonstration-based grasp-planning framework. This framework is designed to extract crucial human grasp skills, namely the contact region and approach direction, from a single demonstration. Then, it formulates an optimization problem that integrates the extracted skills to generate a stable grasp. Distinct from conventional methods that rely on learning implicit synergies t

SUBMITTER: Wang K 

PROVIDER: S-EPMC10819387 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature