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Gripping and holding of objects are key tasks for robotic manipulators. The development of universal grippers able to pick up unfamiliar objects of widely varying shape and surface properties remains, however, challenging. Most current…

This paper is a summary of the recently accomplished research work on flexible gripping systems. The goal is to develop a gripper which can be used for a great amount of geometrically variant workpieces. The economic aspect is of particular…

Robotics · Computer Science 2007-05-23 Michael Sdahl , Bernd Kuhlenkoetter

Handling oversized, variable-shaped, or delicate objects in transportation, grasping tasks is extremely challenging, mainly due to the limitations of the gripper's shape and size. This paper proposes a novel gripper, Lasso Gripper. Inspired…

Robotics · Computer Science 2025-06-18 Qiyuan Qiao , Yu Wang , Xiyu Fan , Peng Lu

Given the laborious difficulty of moving heavy bags of physical currency in the cash center of the bank, there is a large demand for training and deploying safe autonomous systems capable of conducting such tasks in a collaborative…

Many industrial tasks-such as sanding, installing fasteners, and wire harnessing-are difficult to automate due to task complexity and variability. We instead investigate deploying robots in an assistive role for these tasks, where the robot…

Robotics · Computer Science 2024-01-24 Michael Hagenow , Emmanuel Senft , Robert Radwin , Michael Gleicher , Michael Zinn , Bilge Mutlu

Objects grasping, also known as the bin-picking, is one of the most common tasks faced by industrial robots. While much work has been done in related topics, grasping randomly piled objects still remains a challenge because much of the…

Robotics · Computer Science 2020-12-07 Jiaxin Guo , Lian Fu , Mingkai Jia , Kaijun Wang , Shan Liu

This paper presents a physical interface for collaborative mobile manipulators in industrial manufacturing and logistics applications. The proposed work builds on our earlier MOCA-MAN interface, through which an operator could be physically…

Robotics · Computer Science 2023-01-20 Juan M. Gandarias , Pietro Balatti , Edoardo Lamon , Marta Lorenzini , Arash Ajoudani

In cable driven parallel robots (CDPRs), the payload is suspended using a network of cables whose length can be controlled to maneuver the payload within the workspace. Compared to rigid link robots, CDPRs provide better maneuverability due…

Robotics · Computer Science 2025-06-24 Dhruv Sorathiya , Sarthak Sahoo , Vivek Natarajan

Cable-suspended aerial transportation systems are employed extensively across various industries. The capability to flexibly adjust the relative position between the multirotor and the payload has spurred growing interest in the system…

Systems and Control · Electrical Eng. & Systems 2025-10-28 Hai Yu , Zhichao Yang , Wei He , Jianda Han , Yongchun Fang , Xiao Liang

Mobile manipulation robots are continuously advancing, with their grasping capabilities rapidly progressing. However, there are still significant gaps preventing state-of-the-art mobile manipulators from widespread real-world deployments,…

Manipulation planning and control are relevant building blocks of a robotic system and their tight integration is a key factor to improve robot autonomy and allows robots to perform manipulation tasks of increasing complexity, such as those…

Robotic grasping is a fundamental skill across all domains of robot applications. There is a large body of research for grasping objects in table-top scenarios, where finding suitable grasps is the main challenge. In this work, we are…

Robotics · Computer Science 2025-05-13 Martin Rudorfer , Jiří Hartvich , Vojtěch Vonásek

We propose a versatile robotic system for kitting and assembly tasks which uses no jigs or commercial tool changers. Instead of specialized end effectors, it uses its two-finger grippers to grasp and hold tools to perform subtasks such as…

Shape-morphing robots have shown benefits in industrial grasping. We propose form-flexible grippers for adaptive grasping. The design is based on the hybrid jamming and suction mechanism, which deforms to handle objects that vary…

Robotics · Computer Science 2025-07-03 Huijiang Wang , Holger Kunz , Timon Adler , Fumiya Iida

Recent progress in robotic manipulation has dealt with the case of previously unknown objects in the context of relatively simple tasks, such as bin-picking. Existing methods for more constrained problems, however, such as deliberate…

Robotics · Computer Science 2020-06-30 Chaitanya Mitash , Rahul Shome , Bowen Wen , Abdeslam Boularias , Kostas Bekris

For robot arms to perform everyday tasks in unstructured environments, these robots must be able to manipulate a diverse range of objects. Today's robots often grasp objects with either soft grippers or rigid end-effectors. However, purely…

When performing manipulation-based activities such as picking objects, a mobile robot needs to position its base at a location that supports successful execution. To address this problem, prominent approaches typically rely on costly grasp…

Robotics · Computer Science 2024-05-28 Manish Saini , Melvin Paul Jacob , Minh Nguyen , Nico Hochgeschwender

Industrial robots typically require very structured and predictable working environments, and explicit programming, in order to perform well. Therefore, expensive and time-consuming engineering work is a major obstruction when mediating…

Robotics · Computer Science 2019-05-28 Martin Karlsson

This paper presents an integrated system for performing precision harvesting missions using a legged harvester. Our harvester performs a challenging task of autonomous navigation and tree grabbing in a confined, GPS denied forest…

Robotics · Computer Science 2021-11-08 Edo Jelavic , Dominic Jud , Pascal Egli , Marco Hutter

Rearranging and manipulating deformable objects such as cables, fabrics, and bags is a long-standing challenge in robotic manipulation. The complex dynamics and high-dimensional configuration spaces of deformables, compared to rigid…

Robotics · Computer Science 2023-06-21 Daniel Seita , Pete Florence , Jonathan Tompson , Erwin Coumans , Vikas Sindhwani , Ken Goldberg , Andy Zeng
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