477 research outputs found
An adaptive compliance Hierarchical Quadratic Programming controller for ergonomic human–robot collaboration
No full textThis paper proposes a novel Augmented Hierarchical Quadratic Programming (AHQP) framework for multi-tasking control in Human–Robot Collaboration (HRC) which integrates human-related parameters to optimize ergonomics. The aim is to combine parameters that are typical of both industrial applications (e.g. cycle times, productivity) and human comfort (e.g. ergonomics, preference), to identify an optimal trade-off. The augmentation aspect avoids the dependency from a fixed end-effector reference trajectory, which becomes part of the optimization variables and can be used to define a feasible workspace region in which physical interaction can occur. We then demonstrate that the integration of the proposed AHQP in HRC permits the addition of human ergonomics and preference. To achieve this, we develop a human ergonomics function based on the mapping of an ergonomics score, compatible with AHQP formulation. This allows to identify at control level the optimal Cartesian pose that satisfies the active objectives and constraints, that are now linked to human ergonomics. In addition, we build an adaptive compliance framework that integrates both aspects of human preferences and intentions, which are finally tested in several collaborative experiments using the redundant MOCA robot. Overall, we achieve improved human ergonomics and health conditions, aiming at the potential reduction of work-related musculoskeletal disorders
Choosing Poses for Force and Stiffness Control
No full textIn humanoids and other redundant robots interacting with the environment, one can often choose between different configurations and control parameters to achieve a given task. A classic tool to describe specifications of the desired force/displacement behavior in such problems is the stiffness ellipsoid, whose geometry is affected by the choice of parameters in both joint control and redundancy resolution—namely, gains and angles. As is well known, impedance control techniques can regulate gains to realize any desired shape of the Cartesian stiffness ellipsoid at the end-effector, so that robot geometry selection could appear secondary. However, humans do not use this possibility: To control the stiffness of our arms, we predominantly use arm configurations. Why is that, and does it makes sense to do the same in robots? To understand this discrepancy, we provide a more complete analysis of the task-space force/deformation behavior of compliant redundant arms to illustrate why the arm geometry plays a dominant role in interaction capabilities of robots. We introduce the notion of allowable Cartesian force/displacement (“stiffness feasibility”) regions (SFR) for compliant robots with given torque boundaries. We show that different robot configurations modify such regions and explore the role of robot geometry in achieving an appropriate SFR for the task at hand. The novel concepts and definitions are first illustrated in simulations. Experimental results are then provided to verify the effectiveness of the proposed Cartesian force and stiffness control
A Human-in-The-Loop Approach to Robot Action Replanning Through LLM Common-Sense Reasoning
No full textTo facilitate the wider adoption of robotics, accessible programming tools are required for non-experts. Observational learning enables intuitive human skills transfer through hands-on demonstrations, but relying solely on visual input can be inefficient in terms of scalability and failure mitigation, especially when based on a single demonstration. This letter presents a human-in-the-loop method for enhancing the robot execution plan, automatically generated based on a single RGB video, with natural language input to a Large Language Model (LLM). By including user-specified goals or critical task aspects and exploiting the LLM common-sense reasoning, the system adjusts the vision-based plan to prevent potential failures and adapts it based on the received instructions. Experiments demonstrated the framework intuitiveness and effectiveness in correcting vision-derived errors and adapting plans without requiring additional demonstrations. Moreover, interactive plan refinement and hallucination corrections promoted system robustness
Tele-Impedance: Preliminary Results on Measuring and Replicating Human Arm Impedance in Tele Operated Robots
No full textThis work introduces the concept of Tele-Impedance as a method for controlling/teleoperating a robotic arm in contact with the environment. Opposite to bilateral force-reflecting teleoperation control approach, which uses a position/velocity command combined with force feedback from the robot side, Tele-Impedance enriches the command sent to the slave robot by combining the position reference with a stiffness (or full impedance) reference. The desired stiffness profile is directly estimated from the arm of the human operating the remote robotic arm. We preliminarily investigate the effectiveness of this method while teleoperating a slave robotic arm to execute simple tasks. The KUKA light weight robotic arm is used as the slave manipulator. The endpoint (wrist) position of the human arm is monitored by an optical tracking system while the stiffness of the human arm is estimated from the electromyography (EMGs) signal measurements of four flexor-extensor muscle pairs, in realtime. The performance of Tele-Impedance control method is assessed by comparing the results obtained while executing a peg-in-hole task, with the slave arm under i) constant low stiffness, ii) constant high stiffness or iii) under Tele-Impedance control. The experimental results demonstrate the effectiveness of the Tele-Impedance control method and highlight its potential use to safely execute tasks with uncertain environment constraints which may result in large deviations from the commanded position trajectories
Tele-Impedance: Towards Transferring Human Impedance Regulation Skills to Robots
No full textThis work presents the novel concept of Tele-Impedance as a method for controlling/teleoperating a robotic arm while performing tasks which require significant dynamics variation. As an alternative method to bilateral force-reflecting teleoperation control approach, which uses a position/velocity command combined with force feedback from the robot side, Tele-Impedance enriches the command sent to the slave robot by combining the position reference with a stiffness (or full impedance) reference estimated from the arm of the human operator. We propose a new method to estimate the stiffness of the human arm based on the agonist-antagonist muscular co activations. The concept of the Tele-Impedance is demonstrated using the KUKA light weight robotic arm as the slave manipulator in a ball reception experiment. The performance of Tele-Impedance control method is assessed by comparing the results obtained while receiving the ball, with the slave arm under i) constant low stiffness, ii) constant high stiffness or iii) under Tele-Impedance control. Performance indexes are defined and used for the comparative study of the ball reception performances under the different endpoint elastic profiles. The experimental results demonstrate the effectiveness of the task-related Tele-Impedance control method and highlight its potential use to execute tasks which require significant dynamics variation
An Online Method to Detect and Locate an External Load on the Human Body with Applications in Ergonomics Assessment
No full textIn this work, we propose an online method to detect and approximately locate an external load induced on the body of a person interacting with the environment. The method is based on a torque equilibrium condition on the human sagittal plane, which takes into account a reduced-complexity model of the whole-body centre of pressure (CoP) along with the measured one, and the vertical component of the ground reaction forces (vGRFs). The latter is combined with a statistical analysis approach to improve the localisation accuracy, (which is subject to uncertainties) to the extent of the industrial applications we target. The proposed technique eliminates the assumption of known contact position of an external load on the human limbs, allowing a more flexible online body-state tracking. The accuracy of the proposed method is first evaluated via a simulation study in which various contact points on different body postures are considered. Next, experiments on human subjects with three different contact locations applied to the human body are presented, revealing the validity of the proposed methodology. Lastly, its benefit in the estimation of human dynamic states is demonstrated. These results add another layer to the online human ergonomics assessment framework developed in our laboratory, extending it to more realistic and varying interaction conditions
Tele-impedance: Teleoperation with Impedance Regulation Using a Body-Machine Interface
No full textThis work presents the concept of tele-impedance as a method for remotely controlling a robotic arm in interaction
with uncertain environments. As an alternative to bilateral force-reflecting teleoperation control, in tele-impedance a
compound reference command is sent to the slave robot including both the desired motion trajectory and impedance
profile, which are then realized by the remote controller without explicit feedback to the operator. We derive the reference
command from a novel body–machine interface (BMI) applied to the master operator’s arm, using only non-intrusive
position and electromyography (EMG) measurements, and excluding any feedback from the remote site except for looking
at the task. The proposed BMI exploits a novel algorithm to decouple the estimates of force and stiffness of the human
arm while performing the task. The endpoint (wrist) position of the human arm is monitored by an optical tracking
system and used for the closed-loop position control of the robot’s end-effector. The concept is demonstrated in two
experiments, namely a peg-in-the-hole and a ball-catching task, which illustrate complementary aspects of the method.
The performance of tele-impedance control is assessed by comparing the results obtained with the slave arm under either
constantly low or high stiffness
Active gathering of frictional properties from objects
No full textThis work proposes a representation that comprises both shape and friction, as well as the exploration strategy to gather them from an object. The representation is developed under a common probabilistic framework, particularly it uses a Gaussian Process to approximate the distribution of the friction coefficient over the surface, also represented as a Gaussian Process. The surface model is exploited to compute straight lines (geodesic flows) that guide the exploration. The exploration follows these flows by employing an impedance controller in pursuance of safety, shape accommodation and contact enforcement, while measuring the necessary data to estimate the friction coefficient. The exploratory probes consist of an RGBD camera and an Intrinsic Tactile sensor (ITs) mounted on a robotic arm. Experimental results give evidence for the effectiveness of the algorithm in the friction coefficient gathering and enrichment of the object representation
Teleimpedance Control: Overview and Application
No full textIn previous chapters, human hand and arm kinematics have been analyzed through a synergstic approach and the underlying concepts were used to design robotic systems and devise simplified control algorithms. On the other hand, it is well-known that synergies can be studied also at a muscular level as a coordinated activation of multiple muscles acting as a single unit to generate different movements. As a result, muscular activations, quantified through Electromyography (EMG) signals can be then processed and used as direct inputs to external devices with a large number of DOFs. In this chapter, we present a minimalistic approach based on tele-impedance control, where EMGs from only one pair of antagonistic muscle pair are used to map the users postural and stiffness references to the synergy-driven anthropomorphic robotic hand, described in Chap. 7. In this direction, we first provide an overview of the teleimpedance control concept which forms the basis for the development of the hand controller. Eventually, experimental results evaluate the effectiveness of the teleimpedance control concept in execution of the tasks which require significant dynamics variation or are executed in remote environments with dynamic uncertainties
Online Model Based Estimation of Complete Joint Stiffness of Human Arm
No full textThe endpoint stiffness of the human arm has been long recognized as a key component ensuring the quasi-static stability of the arm physical interactions with the external world. Similarly, the understanding of the joint stiffness behavior can provide complementary insights, e.g., on the underlying stiffness regulation principles across different joints including the nullspace stiffness profiles. Traditionally, the experimental modeling and estimation of the human arm joint stiffness is achieved by the transformation of the identified arm endpoint stiffness to the joint coordinates. Due to the underlying kinematic redundancy, the obtained joint stiffness matrix is rank-deficient which implies that the information in the joint stiffness matrix is incomplete. While in robotics applications this issue can be addressed by designing a desired nullspace stiffness behavior through appropriate projections, the use of a similar technique in the identification of human joint stiffness profile is meaningless. Hence, the first objective of this work is to address this issue by developing a novel technique to identify the complete and physiologically meaningful joint stiffness of human arm. Second, we present a model-based online estimation technique to estimate the seven-dimensional complete joint stiffness in various arm poses and activation levels of the two dominant arm muscles that correspond to the geometric and volume modifications of the joint stiffness profile, respectively
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