Luka Peternel

• Ph.D. in Robotics
• Professor (Assistant) at Delft University of Technology

In recent years, providing additional visual feedback about the interaction forces has been found to offer benefits to haptic-assisted teleoperation. However, there is limited insight into the effects of the design of force feedback-related visual cues and the type of visual display on the performance of teleoperation of robotic arms executing indu...

For successful goal-directed human-robot interaction, the robot should adapt to the intentions and actions of the collaborating human. This can be supported by musculoskeletal or data-driven human models, where the former are limited to lower-level functioning such as ergonomics, and the latter have limited generalizability or data efficiency. What...

Robotic devices hold promise for aiding patients in orthopedic rehabilitation. However, current robotic-assisted physiotherapy methods struggle including biomechanical metrics in their control algorithms, crucial for safe and effective therapy. This paper introduces BATON, a Biomechanics-Aware Trajectory Optimization approach to robotic Navigation...

In this work, we propose a method of capturing the patient's discomfort during robotic shoulder physiotherapy, creating "discomfort maps". These maps depict the person-alized distribution of discomfort that each patient perceived across their shoulder range of motion, facilitating both robotic devices and human therapists to account for patient-spe...

Teleoperation is a crucial technology enabling human operators to control robots remotely to perform tasks in hazardous and difficult-to-access environments. Tasks in such environments often involve complex physical interactions with tools and objects of various softness. To this end, teleimpedance enables the operators to adjust the robot impedanc...

Many daily tasks exhibit a periodic nature, necessitating that robots possess the ability to execute them either alone or in collaboration with humans. A widely used approach to encode and learn such periodic patterns from human demonstrations is through periodic Dynamic Movement Primitives (DMPs). Periodic DMPs encode cyclic data independently acr...

This paper presents the design and evaluation of a novel multi-level LLM interface for supermarket robots to assist customers. The proposed interface allows customers to convey their needs through both generic and specific queries. While state-of-the-art systems like OpenAI's GPTs are highly adaptable and easy to build and deploy, they still face c...

In order for off-Earth top surface structures built from regolith to protect astronauts from radiation, they need to be several metres thick. In a feasibility study, funded by the European Space Agency, Technical University Delft (TUD aka TU Delft) explored the possibility of building in empty lava tubes to create rhizomatic subsurface habitats. Wi...

During the learning of a new sensorimotor task, individuals are usually provided with instructional stimuli and relevant information about the target task. The inclusion of haptic devices in the study of this kind of learning has greatly helped in the understanding of how an individual can improve or acquire new skills. However, the way in which th...

Real-world applications of Artificial Intelligence (AI) in architecture have been explored more recently at Technical University (TU) Delft by integrating AI in Design-to-Robotic-Production-Assembly and -Operation (D2RPA&O) methods. These embed robotics into building processes and buildings by linking computational design with robotic construction...

Despite a large body of research on robot learning, it has not yet been thoroughly studied how collaborating humans and robots learn reciprocally. In such situations, both humans and robots continuously learn about each other and the task through interaction. This paper addresses the research question: “How can human-robot co-learning be facilitat...

For successful goal-directed human-robot interaction, the robot should adapt to the intentions and actions of the collaborating human. This can be supported by musculoskeletal or data-driven human models, where the former are limited to lower-level functioning such as ergonomics, and the latter have limited generalizability or data efficiency. What...

The complexity of the human shoulder girdle enables the large mobility of the upper extremity, but also introduces instability of the glenohumeral (GH) joint. Shoulder movements are generated by coordinating large superficial and deeper stabilizing muscles spanning numerous degrees-of-freedom. How shoulder muscles are coordinated to stabilize the m...

Skill propagation among robots without human involvement can be crucial in quickly spreading new physical skills to many robots. In this respect, it is a good alternative to pure reinforcement learning, which can be time-consuming, or learning from human demonstration, which requires human involvement. In the latter case, there may not be enough hu...

Biological systems, including human beings, have the innate ability to perform complex tasks in a versatile and agile manner. Researchers in sensorimotor control have aimed to comprehend and formally define this innate characteristic. The idea, supported by several experimental findings, that biological systems are able to combine and adapt basic u...

The advancement and development of human modeling have greatly benefited from principles used in robotics, for instance, multibody dynamics laid the foundations for physics engines of human movement simulation, and the robotics and control theory were used to contextualize human sensorimotor control. There are many common interests and interconnect...

The complexity of the human shoulder girdle enables the large mobility of the upper extremity, but also introduces instability of the glenohumeral (GH) joint. Shoulder movements are generated by coordinating large superficial and deeper stabilizing muscles spanning numerous degrees-of-freedom. How shoulder muscles are coordinated to stabilize the m...

Daily household tasks involve manipulation in cluttered and unpredictable environments and service robots require complex skills and adaptability to perform such tasks. To this end, we developed a teleoperated online learning approach with a novel skill refinement method, where the operator can make refinements to the initially trained skill by a h...

Humans often demonstrate diverse behaviors due to their personal preferences, for instance, related to their individual execution style or personal margin for safety. In this paper, we consider the problem of integrating both path and velocity preferences into trajectory planning for robotic manipulators. We first learn reward functions that repres...

Collaborative robots (cobots) have the potential to augment the productivity and life quality of human operators in the context of Industry 4.0 by providing them with physical assistance. For this reason, it is necessary to define the relationship between humans and cobots and to study how the two agents adapt to each other. However, to the best of...

Humans often demonstrate diverse behaviors due to their personal preferences, for instance related to their individual execution style or personal margin for safety. In this paper, we consider the problem of integrating such preferences into trajectory planning for robotic manipulators. We first learn reward functions that represent the user path a...

This paper studies non-physical feedback mechanisms to guide human workers toward ergonomic body postures. Specifically, the focus is to solve the tasks that involve no direct physical interaction between the human and the robotic system, therefore tactile guidance by the robot body is not feasible. We propose a multi-modal ergonomic posture guidan...

Performing bimanual tasks with dual robotic setups can drastically increase the impact on industrial and daily life applications. However, performing a bimanual task brings many challenges, such as synchronization and coordination of the single-arm policies. This article proposes the safe, interactive movement primitives learning (SIMPLe) algorithm...

Probably all of us struggle/struggled when learning how to write a good research paper. Especially writing a good Introduction is an art that is difficult to master and even seasoned researchers might still want to improve. I believe that the Introduction is the most important section of the paper since it needs to motivate the reader that the rest...

While half of all construction tasks can be fully automated the other half relies to a certain degree on human support. This paper presents a Computer Vision (CV) and Human–Robot Interaction/Collaboration (HRI/C) supported Design-to-Robotic-Assembly (D2RA) approach that links computational design with robotic assembly. This multidisciplinary approa...

Walking is an essential part of almost all activities of daily living. We use different gait patterns in different situations, e.g., moving around the house, performing various sports, or when compensating for an injury. However, how humans perform this gait tailoring remains a partially unknown process. To this end, the influence of various perfor...

In this work, we propose a method for monitoring and managing rotator-cuff (RC) tendon strains in human-robot collaborative physical therapy for shoulder rehabilitation. We integrate a high-resolution biomechanical model with a collaborative industrial robot arm and an impedance controller to provide feedback to a human subject, therapist or both,...

Performing bimanual tasks with dual robotic setups can drastically increase the impact on industrial and daily life applications. However, performing a bimanual task brings many challenges, like synchronization and coordination of the single-arm policies. This article proposes the Safe, Interactive Movement Primitives Learning (SIMPLe) algorithm, t...

Tele-impedance increases interaction performance between a robotic tool and unstructured/unpredictable environments during teleoperation. However, the existing tele-impedance interfaces have several ongoing issues, such as long calibration times and various obstructions for the human operator. In addition, they are all designed to be controlled by...

In tasks where the goal or configuration varies between iterations, human-robot interaction (HRI) can allow the robot to handle repeatable aspects and the human to provide information which adapts to the current state. Advanced interactive robot behaviors are currently realized by inferring human goal or, for physical interaction, adapting robot im...

In order for off-Earth top surface structures built from regolith to protect astronauts from radiation, they need to be several metres thick. With support from European Space Agency (ESA) and Vertico, the Technical University Delft (TUD) advanced research into constructing habitats in empty lava tubes on Mars in order to create subsurface habitats....

Despite the significant progress made in making robots more intelligent and autonomous, today, teleoperation remains a dominant robot control paradigm for the execution of complex and highly unpredictable tasks. Attempts have been made to make teleoperation systems stable, easy to use, and efficient in terms of physical interactions between the fol...

Space exploration is characterized by a limited amount of resources and tools. This particularly stands out in habitat construction, where heavy machinery like cranes are unavailable and manual work still plays a key role. To mitigate this, we propose a human-robot collaboration method for habitat construction tasks, which involve several key sub-t...

Imitation learning techniques have been used as a way to transfer skills to robots. Among them, dynamic movement primitives (DMPs) have been widely exploited as an effective and an efficient technique to learn and reproduce complex discrete and periodic skills. While DMPs have been properly formulated for learning point-to-point movements for both...

In tele-impedance the human can control the impedance of the remote robot through various interfaces, in addition to controlling the motion. While this can improve the performance of the remote robot in unpredictable and unstructured environments, it can add more workload to the human operator compared to the classic teleoperation. This paper prese...

The existing state-of-the-art interfaces for commanding a remote robot's endpoint stiffness ellipsoid in tele-impedance lack the ability to independently control its size, shape and orientation or they are not easily to implement due to the use of physiological signals, such as electromyography, to control the endpoint stiffness. We propose a novel...

Unlike many traditional stiff position-controlled robots, new collaborative robots interact with humans and operate in an environment that is often unpredictable and unknown. For safe and effective executions of manipulation tasks within such an environment, the robot requires to modulate its compliance. Therefore, the human operator must have a sy...

The science and technology of wearable robots are steadily advancing, and the use of such robots in our everyday life appears to be within reach. Nevertheless, widespread adoption of wearable robots should not be taken for granted, especially since many recent attempts to bring them to real-life applications resulted in mixed outcomes. The aim of t...

Physical human-robot interaction can improve human ergonomics, task efficiency, and the flexibility of automation, but often requires application-specific methods to detect human state and determine robot response. At the same time, many potential human-robot interaction tasks involve discrete modes, such as phases of a task or multiple possible go...

Imitation learning techniques have been used as a way to transfer skills to robots. Among them, dynamic movement primitives (DMPs) have been widely exploited as an effective and an efficient technique to learn and reproduce complex discrete and periodic skills. While DMPs have been properly formulated for learning point-to-point movements for both...

In this work, we explore using computational musculoskeletal modeling to equip an industrial collaborative robot with awareness of the internal state of a patient to safely deliver physical therapy. A major concern of robot-mediated physical therapy is that robots may unwittingly injure patients. For patients with shoulder injuries this typically m...

In this work, we present a novel control approach to human-robot collaboration that takes into account ergonomic aspects of the human co-worker during power tool operations. The method is primarily based on estimating and reducing the overloading torques in the human joints that are induced by the manipulated external load. The human overloading jo...

Teaching robots how to apply forces according to our preferences is still an open challenge that has to be tackled from multiple engineering perspectives. This paper studies how to learn variable impedance policies where both the Cartesian stiffness and the attractor can be learned from human demonstrations and corrections with a user-friendly inte...

Biological systems, including human beings, have the innate ability to perform complex tasks in versatile and agile manner. Researchers in sensorimotor control have tried to understand and formally define this innate property. The idea, supported by several experimental findings, that biological systems are able to combine and adapt basic units of...

Tele-impedance augments classic teleoperation by enabling the human operator to actively command remote robot stiffness in real-time, which is an essential ability to successfully interact with the unstructured and unpredictable environment. However, the literature is missing a study on benefits and drawbacks of different types of stiffness command...

Ergonomics of human workers is one of the key elements in design and evaluation of production processes. Human ergonomics have a major impact on productivity as well as chronic health risks incurred by inappropriate working postures and conditions. In this paper we propose a novel method for estimating and communicating the ergonomic work condition...

In this paper, we introduce and explore a concept called coupling effect, which pertains to the influence of force feedback on the commanded stiffness that is voluntarily controlled by the operator through the stiffness interface during bilateral tele-impedance. The degree of coupling effect depends on the type of interface used to control the impe...

In this paper, we propose a method for improving the human operator's arm posture during bilateral teleoperation. The method is based on a musculoskeletal model that considers human operator's arm dynamics and the feedback force from the haptic interface (master), which is used to control a robotic arm (slave) in a remote environment. We perform an...

Goal-directed human reaching often involves multi-component strategy with sub-movements. In general, the initial sub-movement is fast and less precise to bring the limb’s endpoint in the vicinity of the target as soon as possible. The final sub-movement then corrects the error accumulated during the previous sub-movement in order to reach the targe...

Safety and health of human workers are always the most important factors in the design and evaluation of a human-involved production process. While safety is usually associated with physical injuries instantly caused by collisions or impacts between human workers and machinery, ergonomics or human factors are more concerned with chronic health risk...

In this paper, we propose a method for selective monitoring and management of human muscle fatigue in human-robot co-manipulation scenarios. The proposed approach uses a machine learning technique to learn the complex relationship between individual human muscle forces, arm configuration and arm endpoint force that are provided by a sophisticated o...

The deployment of industrial robotic cells based on lean manufacturing principles enables the development of fast-reconfigurable assembly lines in which human and robotic agents collaborate to achieve a shared task. To ensure the effective coordination of the shared effort, each task must be decomposed into a sequence of atomic actions that can be...

This paper introduces a novel control framework for an arm exoskeleton that takes into account force of the human arm. In contrast to the conventional exoskeleton controllers where the assistance is provided without considering the human arm biomechanical force manipulability properties, we propose a control approach based on the arm muscular manip...

Musculoskeletal disorders, the single largest category of workrelated injuries in many industrial countries, are associated with very high costs in terms of lost productivity. In highvolume production facilities, large parts of the workstation should ideally be adapted to individual workers in real time to prevent such injuries. However, in smaller...

Stairways, public transport, and inclined walkways are often considered as sites with higher likelihood of falls due to a sudden loss of balance. Such sites are usually marked with warning signs, equipped with non-slip surfaces and handles or handrails to avert or decrease this likelihood. Especially handles are supposed to provide additional suppo...

The improved adaptability of a robotic teleoperation system to unexpected disturbances in remote environments can be achieved by compliance control. Nevertheless, complying with all types of interaction forces while performing realistic manipulation tasks may deteriorate the teleoperation performance. For instance, the loading effect of the objects...

In this paper, we propose a novel method for selective management of muscle fatigue in human-robot co-manipulation. The proposed framework enables the detection of excessive fatigue levels of an individual muscle group while executing a certain task, and provides anticipatory robotic responses to distribute the effort among less-fatigued muscles of...

Collaborative robots are often designed with limited power and force capacity, with the aim to provide affordable solutions and ensure human safety in case of accidental collisions and impacts. If a task requires a power beyond this capacity, or is performed repeatedly over long periods, such limits may be exceeded, which can cause inevitable robot...

In this paper, we propose a novel method for human–robot collaboration, where the robot physical behaviour is adapted online to the human motor fatigue. The robot starts as a follower and imitates the human. As the collaborative task is performed under the human lead, the robot gradually learns the parameters and trajectories related to the task ex...

[This corrects the article on p. 615 in vol. 11, PMID: 29379424.].

[This corrects the article on p. 615 in vol. 11, PMID: 29379424.].

We propose a novel human-in-the-loop approach for teaching robots how to solve assembly tasks in unpredictable and unstructured environments. In the proposed method the human sensorimotor system is integrated into the robot control loop though a teleoperation setup. The approach combines a 3-DoF end-effector force feedback with an interface for mod...

Two basic trade-offs interact while our brain decides how to move our body. First, with the cost-benefit trade-off, the brain trades between the importance of moving faster toward a target that is more rewarding and the increased muscular cost resulting from a faster movement. Second, with the speed-accuracy trade-off, the brain trades between how...

In this paper we propose a semi-autonomous control framework for manipulation tasks that is focused on debris removal setups. The proposed method enables an efficient and safe removal of long stick-like shaped debris. The manipulation module includes seven motion primitives. Due to the inevitability of natural/man-made disasters, the development of...

In this paper we study the concept of robots learning from collaboration with skilled robots. The advantage of this concept is that the human involvement is reduced, while the skill can be propagated faster among the robots performing similar collaborative tasks or the ones being executed in hostile environments. The expert robot initially obtains...

In this paper, we propose a novel method for the control of human-robot co-manipulation that takes into account the ergonomic requirements for the human co-worker. The robot uses a whole-body dynamic model of the human to optimise for the position of the co-manipulation task in the workspace. In this configuration, the overloading joint torques, i....

This paper proposes a novel human-robot collaboration (HRC) control approach to alert and reduce the static joint torque overloading of a human partner while executing shared tasks with a robot. Using a pre-identified statically equivalent serial chain (SESC) model, variations of the centre-of-pressure and ground reaction force are calculated, and...

This paper aims to improve the interaction and coordination between the human and the robot in cooperative execution of complex, powerful and dynamic tasks. We propose a novel approach that integrates online information about the human motor function and manipulability properties into the hybrid controller of the assistive robot. Through this human...

In this paper we propose a novel method that enables the robot to autonomously devise an appropriate control strategy from human demonstrations without a prior knowledge of the demonstrated task. The method is primarily based on observing the patterns and consistency in the observed dataset. This is obtained through a demonstration setting that use...

In this paper, we propose a method that allows the robot to adapt its physical behaviour to the human fatigue in human-robot co-manipulation tasks. The robot initially imitates the human to perform the collaborative task in a leader-follower setting, using a feedback about the human motor behaviour. Simultaneously, the robot obtains the skill in on...

This paper presents a novel approach for human-robot cooperation in tasks with dynamic uncertainties. The essential element of the proposed method is a multi-modal interface that provides the robot with the feedback about the human motor behaviour in real-time. The human muscle activity measurements and the arm force manipulability properties encod...

When balance is exposed to perturbations, hand contacts are often used to assist postural control. We investigated the immediate and the transitionary effects of supportive hand contacts during continuous anteroposterior perturbations of stance by automated waist-pulls. Ten young adults were perturbed for 5 min and required to maintain balance by h...

In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the...

Video of qualitative validation experiments. The video shows the experiments on elbow exoskeleton and whole-arm exoskeleton using a trained subject as described in the paper. (MP4)

Exoskeletons are successful at supporting human motion only when the necessary amount of power is provided at the right time. Exoskeleton control based on EMG signals can be utilized to command the required amount of support in real-time. To this end, one needs to map human muscle activity to the desired task-specific exoskeleton torques. In order...