Kensuke Harada

Xinyi Zhang

Yukiyasu Domae

Weiwei Wan

This book introduces methods for bin picking in manufacturing. These methods can be used to develop unified, dexterous, and robust bin picking systems for entangled objects. The target objects include both rigid and deformable objects. Robotic bin picking is a valuable task in manufacturing, aiming to automate the assembly process by utilizing robots to pick necessary objects from disorganized bins. Previous studies have addressed various challenges related to bin picking. However, when objects with complex shapes or deformable properties are randomly placed in a bin, they tend to get entangled, making it difficult for the robot to pick up individual items. This poses challenges in perception, as the robot must be capable of distinguishing between isolated objects and potentially tangled ones in a cluttered environment. This book is of interest to students, researchers, and professionals in manufacturing industries.

Robotic Bin Picking for Potentially Tangled Objects

Eiichi Yoshida

Kazuhito Yokoi

Research on humanoid robots has been mostly with the aim of developing robots that can replace humans in the performance of certain tasks. Motion planning for these robots can be quite difficult, due to their complex kinematics, dynamics and environment. It is consequently one of the key research topics in humanoid robotics research and the last few years have witnessed considerable progress in the field. Motion Planning for Humanoid Robots surveys the remarkable recent advancement in both the theoretical and the practical aspects of humanoid motion planning. Various motion planning frameworks are presented in Motion Planning for Humanoid Robots, including one for skill coordination and learning, and one for manipulating and grasping tasks. The problem of planning sequences of contacts that support acyclic motion in a highly constrained environment is addressed and a motion planner that enables a humanoid robot to push an object to a desired location on a cluttered table is described. The main areas of interest include: • whole body motion planning, • task planning, • biped gait planning, and • sensor feedback for motion planning. Torque-level control of multi-contact behavior, autonomous manipulation of moving obstacles, and movement control and planning architecture are also covered. Motion Planning for Humanoid Robots will help readers to understand the current research on humanoid motion planning. It is written for industrial engineers, advanced undergraduate and postgraduate students.

Kensuke Harada

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