Oct 2026· e+i Elektrotechnik und Informationstechnik· Vol 143, pp. 521 - 533· 0 citations· 33 references
TL;DR
This paper compares a conventional workcell with fixed robotic arms equipped with parallel grippers, and external vision, against a humanoid robot equipped with three-finger hands and onboard RGB‑D sensing, and assesses the differences in both use cases.
Abstract
Robotic manipulation has traditionally relied on fixed-base robotic arms with parallel grippers and external sensors for structured and repetitive tasks, which could be mounted on mobile platforms. Recent advances in limb-based locomotion and dexterous end effectors are enabling a shift toward mobile humanoid platforms. This paper examines the opportunities and challenges of that transition based on the state-of-the art in 2026 on the use case of sorting mixed textiles from an unordered heap into designated bins. We compare a conventional workcell with fixed robotic arms equipped with parallel grippers, and external vision, against a humanoid robot equipped with three-finger hands and onboard RGB‑D sensing. We assess the differences in both use cases regarding deployment flexibility, workspace reachability, safety certification, reliability and in-hand manipulation. As a preliminary step, we define a perception–manipulation pipeline for deformable objects and identify key bottlenecks that currently limit performance: category classification, grasp stability on textiles and whole-body motion planning. We conclude with an outlook on the maturity of current humanoid systems and outline the technical and regulatory steps needed for their integration into textile sorting and related industrial domains.
Current humanoid dexterous manipulation remains largely confined to end-effectors and simple grasps, falling short of humans'ability to engage the entire body by bracing and sliding bulky objects against the arms and torso. We introduce Whole-Body Dexterity (WBD), a general framework that uses the robot's body and appe...
Conor Mc Gartoll, An Dang, Pranay Thangeda et al.· 0 citations
Many manipulation tasks that are effortless for dexterous human hands remain challenging for robotic systems equipped with simple, task-specialized grippers. Industrial platforms commonly rely on end-effectors such as suction cups or parallel-jaw grippers, yet no single mode can reliably satisfy the diverse constraints...
Sukhvansh Jain, Anurag Maurya, Shivam Vats et al.· 0 citations
Human video offers a scalable source of robot demonstrations, yet most human-to-humanoid retargeting methods assume a legged robot with human-like kinematics. This assumption does not hold for mobile-base humanoids equipped with a wheeled base, vertical lift, and two arms. Human walking must be expressed through base m...
Jiyeon Koo, Eunseom Pyo, Jeonghee Seo et al.· 0 citations
In this paper, we present a mobile manipulation system for humanoid robots to solve industrial part-sorting tasks, in which the robot needs to pick up a part from one workstation and transport it to another. Several functional modules are included in the system. The lower-body control module comprises locomotion and na...
Jie Ren, Jia-Yang Wu, Long-Chang Yu et al.· IEEE Transactions on Automat...· 0 citations
Robot hands are a key interface between AI and the physical world, making advances in robotic dexterity essential to realizing the vision of physical AI. While impressive dexterity has been demonstrated with simple grippers, multifingered hands offer the potential for substantially greater versatility, precision, and a...
Anthony Shilati, Anu Ramaswami, Luke C. Batteas et al.· 0 citations
An experimental setup to collect arm and hand movement data from humans using a set of Color and Color and Depth cameras via MediaPipe, but without needing any markers is proposed, so that several daily human manipulation tasks can be mimicked, recorded and used for training to eventually enable full autonomy in the fu...