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In this article, we propose Echo, a novel joint-matching teleoperation system designed to enhance the collection of datasets for manual and bimanual tasks. Our system is specifically tailored for controlling the UR manipulator and features…
Component inspection is often the bottleneck in high-value manufacturing, driving industries like aerospace toward automated inspection technologies. Current systems often employ fixed arm robots, but they lack the flexibility in adapting…
Individualized manufacturing of cars requires kitting: the collection of individual sets of part variants for each car. This challenging logistic task is frequently performed manually by warehouseman. We propose a mobile manipulation…
This paper introduces iRoCo (intuitive Robot Control) - a framework for ubiquitous human-robot collaboration using a single smartwatch and smartphone. By integrating probabilistic differentiable filters, iRoCo optimizes a combination of…
ALOHA2 is an enhanced version of the dual-arm teleoperated robot ALOHA, featuring higher performance and robustness compared to the original design, while also being more ergonomic. Like ALOHA, ALOHA2 consists of two grippers and two ViperX…
Long-horizon navigation in complex urban environments relies heavily on continuous human operation, which leads to fatigue, reduced efficiency, and safety concerns. Shared autonomy, where a Vision-Language AI agent and a human operator…
Teleoperation is a critical method for human-robot interface, holds significant potential for enabling robotic applications in industrial and unstructured environments. Existing teleoperation methods have distinct strengths and limitations…
This paper presents the development of a control system for vision-guided pick-and-place tasks using a robot arm equipped with a 3D camera. The main steps include camera intrinsic and extrinsic calibration, hand-eye calibration, initial…
Space robots have played a critical role in autonomous maintenance and space junk removal. Multi-arm space robots can efficiently complete the target capture and base reorientation tasks due to their flexibility and the collaborative…
General-purpose robots must master long-horizon manipulation, defined as tasks involving multiple kinematic structure changes (e.g., attaching or detaching objects) in unstructured environments. While Vision-Language-Action (VLA) models…
With the continuous advancement of robot teleoperation technology, shared control is used to reduce the physical and mental load of the operator in teleoperation system. This paper proposes an alternating shared control framework for object…
In this work we extend the low-cost GELLO teleoperation system, initially designed for joint position control, with additional force information. Our first extension is to implement force feedback, allowing users to feel resistance when…
This paper proposes a common interface for real-time low-level motion planning of collaborative robotic arms, aimed at enabling broader applicability and improved portability across heterogeneous hardware platforms. In previous work, we…
Legged manipulators, such as quadrupeds equipped with robotic arms, require motion planning techniques that account for their complex kinematic constraints in order to perform manipulation tasks both safely and effectively. However,…
We present UniBiDex a unified teleoperation framework for robotic bimanual dexterous manipulation that supports both VRbased and leaderfollower input modalities UniBiDex enables realtime contactrich dualarm teleoperation by integrating…
Humanoid robot teleoperation allows humans to integrate their cognitive capabilities with the apparatus to perform tasks that need high strength, manoeuvrability and dexterity. This paper presents a framework for teleoperation of humanoid…
Augmented Reality and Virtual Reality can provide to a Human Operator (HO) a real help to complete complex tasks, such as robot teleoperation and cooperative teleassistance. Using appropriate augmentations, the HO can interact faster, safer…
Tactile sensing is essential for robots to achieve human-like gentle manipulation. However, existing Vision-Language-Action (VLA) models struggle to exploit tactile feedback for gentle manipulation due to scarce aligned…
Reinforcement learning (RL) is effective in many robotic applications, but it requires extensive exploration of the state-action space, during which behaviors can be unsafe. This significantly limits its applicability to large robots with…
We present a cross robot visuomotor learning framework that integrates diffusion policy based control with 3D semantic scene representations from D3Fields to enable category level generalization in manipulation. Its modular design supports…