Admittance-Based Motion Planning with Vision-Guided Initialization for Robotic Manipulators in Self-Driving Laboratories
Department of Electronics Systems, Aalborg University（电子系统系，奥尔堡大学）；Department of Information Technology and Electrical Engineering, Università degli Studi di Napoli Federico II（信息科技与电气工程系，那不勒斯费迪里奇二世大学）
Shifa Sulaiman, Tobias Jensen, Francesco Schetter, Simon Bøgh
Self driving laboratories (SDLs) are highly automated research environments that leverage advanced technologies to conduct experiments and analyze data with minimal human involvement. These environments often involve delicate laboratory equipment, unpredictable environmental interactions, and occasional human intervention, making compliant and force aware control essential for ensuring safety, adaptability, and reliability. This paper introduces a motion-planning framework centered on admittance control to enable adaptive and compliant robotic manipulation. Unlike conventional schemes, the proposed approach integrates an admittance controller directly into trajectory execution, allowing the manipulator to dynamically respond to external forces during interaction. This capability enables human operators to override or redirect the robot's motion in real time. A vision algorithm based on structured planar pose estimation is employed to detect and localize textured planar objects through feature extraction, homography estimation, and depth fusion, thereby providing an initial target configuration for motion planning. The vision based initialization establishes the reference trajectory, while the embedded admittance controller ensures that trajectory execution remains safe, adaptive, and responsive to external forces or human intervention. The proposed strategy is validated using textured image detection as a proof of concept. Future work will extend the framework to SDL environments involving transparent laboratory objects where compliant motion planning can further enhance autonomy, safety, and human-robot collaboration.
Queen’s University of Belfast（贝尔法斯特女王大学）；University of Warwick（华威大学）
This paper proposes a novel fixed-time integral sliding mode controller for admittance control to enhance physical human-robot collaboration. The proposed method combines the benefits of compliance to external forces of admittance control and high robustness to uncertainties of integral sliding mode control (ISMC), such that the system can collaborate with a human partner in an uncertain environment effectively. Firstly, a fixed-time sliding surface is applied in the ISMC to make the tracking error of the system converge within a fixed-time regardless of the initial condition. Then, a fixed-ti…
Although autonomous control of robotic manipulators has been studied for several decades, they are not commonly used in safety-critical applications due to lack of safety and performance guarantees - many of them concerning the modulation of interaction forces. This paper presents a mechanical probing strategy for estimating the environmental impedance parameters of compliant environments, independent a manipulator's controller design, and configuration. The parameter estimates are used in a position-based adaptive force controller to enable control of interaction forces in compliant, stationa…
Physical Human-Robot Interaction (pHRI) task involves tight coupling between safety constraints and compliance with human intentions. In this paper, a novel switched model reference admittance controller is developed to maintain compliance with the external force while upholding safety constraints in the workspace for an n-link manipulator involved in pHRI. A switched reference model is designed for the admittance controller to generate the reference trajectory within the safe workspace. The stability analysis of the switched reference model is carried out by an appropriate selection of the Co…
University of Modena and Reggio Emilia（摩德纳-雷焦艾米利亚大学）
During physical human robot collaboration, it is important to be able to implement a time-varying interactive behaviour while ensuring robust stability. Admittance control and passivity theory can be exploited for achieving these objectives. Nevertheless, when the admittance dynamics is time-varying, it can happen that, for ensuring a passive and stable behaviour, some spurious dissipative effects have to be introduced in the admittance dynamics. These effects are perceived by the user and degrade the collaborative performance. In this paper we exploit the task redundancy of the manipulator in…
Aristotle University of Thessaloniki（塞萨洛尼基亚里士多德大学）
The restriction of feasible motions of a manipulator link constrained to move through an entry port is a common problem in minimum invasive surgery procedures. Additional spatial restrictions are required to ensure the safety of sensitive regions from unintentional damage. In this work, we design a target admittance model that is proved to enforce robot tool manipulation by a human through a remote center of motion and to guarantee that the tool will never enter or touch forbidden regions. The control scheme is proved passive under the exertion of a human force ensuring manipulation stability,…
Istituto Italiano di Tecnologia（意大利理工学院）；Politecnico di Milano（米兰理工大学）
This paper proposes a hybrid learning and optimization framework for mobile manipulators for complex and physically interactive tasks. The framework exploits an admittance-type physical interface to obtain intuitive and simplified human demonstrations and Gaussian Mixture Model (GMM)/Gaussian Mixture Regression (GMR) to encode and generate the learned task requirements in terms of position, velocity, and force profiles. Next, using the desired trajectories and force profiles generated by GMM/GMR, the impedance parameters of a Cartesian impedance controller are optimized online through a Quadra…
Queen’s University Belfast（贝尔法斯特女王大学）；University of Warwick（华威大学）
Physical human-robot collaboration requires strict safety guarantees since robots and humans work in a shared workspace. This letter presents a novel control framework to handle safety-critical position-based constraints for human-robot physical interaction. The proposed methodology is based on admittance control, exponential control barrier functions (ECBFs) and quadratic program (QP) to achieve compliance during the force interaction between human and robot, while simultaneously guaranteeing safety constraints. In particular, the formulation of admittance control is rewritten as a second-ord…
Baxalta Innovations GmbH, a Takeda company（巴克斯特创新有限公司（武田制药旗下公司））；Antal Bejczy Center for Intelligent Robotics, Óbuda University（欧布达大学安塔尔·贝伊奇智能机器人中心）
Increasing the level of automation in pharmaceutical laboratories and production facilities plays a crucial role in delivering medicine to patients. However, the particular requirements of this field make it challenging to adapt cutting-edge technologies present in other industries. This article provides an overview of relevant approaches and how they can be utilized in the pharmaceutical industry, especially in development laboratories. Recent advancements include the application of flexible mobile manipulators capable of handling complex tasks. However, integrating devices from many differen…
The University of Texas at Austin（德克萨斯大学奥斯汀分校）；Argonne National Laboratory（阿贡国家实验室）
In nuclear isotope and chemistry laboratories, hot cells and gloveboxes provide scientists with a controlled and safe environment to perform experiments. Working on experiments in these isolated containment cells requires scientists to be physically present. For hot cell work today, scientists manipulate equipment and radioactive material inside through a bilateral mechanical control mechanism. Motions produced outside the cell with the master control levers are mechanically transferred to the internal grippers inside the shielded containment cell. There is a growing need to have the capabilit…
In this work, we introduce an adaptive control framework for human-robot collaborative transportation of objects with unknown deformation behaviour. The proposed framework takes as input the haptic information transmitted through the object, and the kinematic information of the human body obtained from a motion capture system to create reactive whole-body motions on a mobile collaborative robot. In order to validate our framework experimentally, we compared its performance with an admittance controller during a co-transportation task of a partially deformable object. We additionally demonstrat…
Institut de Robòtica i Informàtica Industrial, CSIC-UPC（西班牙国家研究委员会-加泰罗尼亚理工大学工业机器人与计算机视觉研究所）
Transferring human motion to a mobile robotic manipulator and ensuring safe physical human-robot interaction are crucial steps towards automating complex manipulation tasks in human-shared environments. In this work, we present a novel human to robot whole-body motion transfer framework. We propose a general solution to the correspondence problem, namely a mapping between the observed human posture and the robot one. For achieving real-time imitation and effective redundancy resolution, we use the whole-body control paradigm, proposing a specific task hierarchy, and present a differential driv…
ETH Zurich（苏黎世联邦理工学院）；LAAS-CNRS（法国国家科学研究中心分析与系统架构实验室）；Université de Toulouse（图卢兹大学）；CNRS（法国国家科学研究中心）；University of Naples Federico II（那不勒斯费德里科二世大学）
Today, physical Human-Robot Interaction (pHRI) is a very popular topic in the field of ground manipulation. At the same time, Aerial Physical Interaction (APhI) is also developing very fast. Nevertheless, pHRI with aerial vehicles has not been addressed so far. In this work, we present the study of one of the first systems in which a human is physically connected to an aerial vehicle by a cable. We want the robot to be able to pull the human toward a desired position (or along a path) only using forces as an indirect communication-channel. We propose an admittance-based approach that makes pHR…
Osaka University（大阪大学）；National Institute of Advanced Industrial Science and Technology (AIST)（日本产业技术综合研究所）；FUJIFILM Corporation（富士胶片公司）；Nara Institute of Science and Technology (NAIST)（奈良先端科学技术大学院大学）
Reinforcement Learning (RL) methods have been proven successful in solving manipulation tasks autonomously. However, RL is still not widely adopted on real robotic systems because working with real hardware entails additional challenges, especially when using rigid position-controlled manipulators. These challenges include the need for a robust controller to avoid undesired behavior, that risk damaging the robot and its environment, and constant supervision from a human operator. The main contributions of this work are, first, we proposed a learning-based force control framework combining RL t…
Robotic System for Chemical Experiment Automation with Dual Demonstration of End-effector and Jig Operations
Division of Information, Science Graduate School of Science and Technology（信息科学研究生院）；Nara Institute of Science and Technology（奈良科学技术大学）；Materials Informatics Initiative, RD technology and digital transformation center（材料信息学计划，RD技术与数字化转型中心）；JSR Corporation（JSR公司）；Fine Chemical Process Dept., JSR Corporation（JSR公司精细化学工艺部门）；Department of Chemistry Faculty of Science and Technology（科学与技术学部化学系）；Keio University（庆应义塾大学）；Data Science Center（数据科学中心）；Division of Materials Science, Graduate School of Science and Technology（材料科学系，研究生院）
