This paper presents a novel interaction planning method that exploits impedance tuning techniques in response to environmental uncertainties and unpredictable conditions using haptic information only. The proposed algorithm plans the robot's trajectory based on the haptic interaction with the environment and adapts planning strategies as needed. Two approaches are considered: Exploration and Bouncing strategies. The Exploration strategy takes the actual motion of the robot into account in planning, while the Bouncing strategy exploits the forces and the motion vector of the robot. Moreover, self-tuning impedance is performed according to the planned trajectory to ensure compliant contact and low contact forces. In order to show the performance of the proposed methodology, two experiments with a torque-controller robotic arm are carried out. The first considers a maze exploration without obstacles, whereas the second includes obstacles. The proposed method performance is analyzed and compared against previously proposed solutions in both cases. Experimental results demonstrate that: i) the robot can successfully plan its trajectory autonomously in the most feasible direction according to the interaction with the environment, and ii) a compliant interaction with an unknown environment despite the uncertainties is achieved. Finally, a scalability demonstration is carried out to show the potential of the proposed method under multiple scenarios.
Learning-based Force Sensing and Impedance Matching for Safe Haptic Feedback in Robot-assisted Laparoscopic Surgery
organization= Surgical Robotics Laboratory (SRL), Mechanical Engineering Department, Concordia University , city= Montreal , state= QC , country= Canada；Robotics (SuPER) Centre, Department of Surgery, McGill University , city= Montreal , state= QC , country= Canada；Joyce Posluns Centre for Image Guided Innovation \& Therapeutic Intervention (PCIGITI), The Hospital for Sick Children (SickKids) , city= Toronto , state= ON , country= Canada
This paper evaluates the capabilities of a soft robotic pneumatic actuator derived from the terrain display haptic device, "The Smart Shoe." The bladder design of the Smart Shoe is upgraded to include a pressure supply and greater output flow capabilities. A bench top setup is created to rigorously test this new type of actuator. The bandwidth and stiffness capability of this new actuator are evaluated relative to forces and displacements encountered during human gait. Four force vs. displacement profiles relevant to haptic terrain display are proposed and tested using sliding-mode tracking co…
University of North Carolina at Charlotte（北卡罗来纳大学夏洛特分校）；University of Michigan（密歇根大学）
Communication and cooperation among team members can be enhanced significantly with physical interaction. Successful collaboration requires the integration of the individual partners' intentions into a shared action plan, which may involve a continuous negotiation of intentions and roles. This paper presents an adaptive haptic shared control framework wherein a human driver and an automation system are physically connected through a motorized steering wheel. By virtue of haptic feedback, the driver and automation system can monitor each other actions and can still intuitively express their con…
Amirkabir University of Technology (Tehran Polytechnic)（阿米尔卡比尔理工大学（德黑兰理工大学））；Sharif University of Technology（谢里夫理工大学）
Haptic training simulators generally consist of three major components, namely a human operator, a haptic interface, and a virtual environment. Appropriate dynamic modeling of each of these components can have far-reaching implications for the whole system's performance improvement in terms of transparency, the analogy to the real environment, and stability. In this paper, we developed a virtual-based haptic training simulator for Endoscopic Sinus Surgery (ESS) by doing a dynamic characterization of the phenomenological sinus tissue fracture in the virtual environment, using an input-constrain…
Robotic teleoperation will allow us to perform complex manipulation tasks in dangerous or remote environments, such as needed for planetary exploration or nuclear decommissioning. This work proposes a novel telemanipulation architecture using a passive Fractal Impedance Controller (FIC), which does not depend upon an active viscous component for stability guarantees. Compared to a traditional impedance controller in ideal conditions (no delays and maximum communication bandwidth), our proposed method yields higher transparency in interaction and demonstrates superior dexterity and capability i…
Adaptive Manipulation Potential and Haptic Estimation for Tool-Mediated Interaction
School of Mechanical and Aerospace Engineering, Nanyang Technological University（南洋理工大学机械与航空航天工程学院）；Imperial College of Science, Technology and Medicine（帝国理工学院科学、技术与医学学院）
Force estimation using neural networks is a promising approach to enable haptic feedback in minimally invasive surgical robots without end-effector force sensors. Various network architectures have been proposed, but none have been tested in real time with surgical-like manipulations. Thus, questions remain about the real-time transparency and stability of force feedback from neural network-based force estimates. We characterize the real-time impedance transparency and stability of force feedback rendered on a da Vinci Research Kit teleoperated surgical robot using neural networks with vision-…
Skoltech（斯科尔科沃科技学院）；Imperial College London（伦敦帝国学院）
To achieve high fidelity haptic rendering of soft objects in a high mobility virtual environment, we propose a novel haptic display DandelionTouch. The tactile actuators are delivered to the fingertips of the user by a swarm of drones. Users of DandelionTouch are capable of experiencing tactile feedback in a large space that is not limited by the device's working area. Importantly, they will not experience muscle fatigue during long interactions with virtual objects. Hand tracking and swarm control algorithm allow guiding the swarm with hand motions and avoid collisions inside the formation. S…
University of Sussex（萨塞克斯大学）；University of Edinburgh（爱丁堡大学）
The teleoperation of robots enables remote intervention in distant and dangerous tasks without putting the operator in harm's way. However, remote operation faces fundamental challenges due to limits in communication delays. The proposed work improves the performances of teleoperation architecture based on Fractal Impedance Controller (FIC) by integrating into the haptic teleoperation pipeline a postural optimisation that also accounts for the replica robots' physical limitations. This update improves dynamic interactions by trading off tracking accuracy to maintain the system within its power…
University of Heidelberg（海德堡大学）；University of Genoa（热那亚大学）；University Niccolò Cusano（尼可洛·库萨诺大学）
Bimanual object manipulation involves multiple visuo-haptic sensory feedbacks arising from the interaction with the environment that are managed from the central nervous system and consequently translated in motor commands. Kinematic strategies that occur during bimanual coupled tasks are still a scientific debate despite modern advances in haptics and robotics. Current technologies may have the potential to provide realistic scenarios involving the entire upper limb extremities during multi-joint movements but are not yet exploited to their full potential. The present study explores how hands…
Institute of Perception, Action and Behaviour, School of Informatics, The University of Edinburgh（爱丁堡大学信息学院感知、行动与行为研究所）；Oxford Robotics Institute at the University of Oxford（牛津大学牛津机器人研究所）；School of Computer Science/Department of Electrical and Computer Engineering at McGill University（麦吉尔大学计算机科学学院/电气与计算机工程系）
This paper presents a control framework to teleoperate a quadruped robot's foot for operator-guided haptic exploration of the environment. Since one leg of a quadruped robot typically only has 3 actuated degrees of freedom (DoFs), the torso is employed to assist foot posture control via a hierarchical whole-body controller. The foot and torso postures are controlled by two analytical Cartesian impedance controllers cascaded by a null space projector. The contact forces acting on supporting feet are optimized by quadratic programming (QP). The foot's Cartesian impedance controller may also esti…
In this paper, we present a planning framework that uses a combination of implicit (robot motion) and explicit (visual/audio/haptic feedback) communication during mobile robot navigation. First, we developed a model that approximates both continuous movements and discrete behavior modes in human navigation, considering the effects of implicit and explicit communication on human decision making. The model approximates the human as an optimal agent, with a reward function obtained through inverse reinforcement learning. Second, a planner uses this model to generate communicative actions that max…
University of Edinburgh（爱丁堡大学）；University of Oxford（牛津大学）
The ability of animals to interact with complex dynamics is unmatched in robots. Especially important to the interaction performances is the online adaptation of body dynamics, which can be modeled as an impedance behaviour. However, the variable impedance controller still possesses a challenge in the current control frameworks due to the difficulties of retaining stability when adapting the controller gains. The fractal impedance controller has been recently proposed to solve this issue. However, it still has limitations such as sudden jumps in force when it starts to converge to the desired …
The utility of Human-in-the-loop telerobotic systems (HiLTS) is driven in part by the quality of feedback it can provide to the operator. While the dynamic interaction between robot and environment can often be sensed or modeled, the dynamic coupling of the human-robot interface is often overlooked. Enabling dexterous manipulation through HiLTS however, will require careful consideration of human haptic perception as it relates to the human's changing limb impedance at the human-robot interface. In this manuscript, we present results from a stiffness perception task run on a simple 1-DoF rotat…
Siemens Corporate Technology（西门子中央研究院）；University of Freiburg（弗莱堡大学）
In automated manufacturing, robots must reliably assemble parts of various geometries and low tolerances. Ideally, they plan the required motions autonomously. This poses a substantial challenge due to high-dimensional state spaces and non-linear contact-dynamics. Furthermore, object poses and model parameters, such as friction, are not exactly known and a source of uncertainty. The method proposed in this paper models the task of parts assembly as a belief space planning problem over an underlying impedance-controlled, compliant system. To solve this planning problem we introduce an asymptoti…
HetSwarm: Cooperative Navigation of Heterogeneous Swarm in Dynamic and Dense Environments through Impedance-based Guidance
Intelligent Space Robotics Laboratory, Center for Digital Engineering, Skolkovo Institute of Science and Technology（斯克尔科夫科学与技术研究所智能空间机器人实验室，数字工程中心）；Multi-Robot Autonomy Laboratory, Department of Data Science and Engineering, IISER Bhopal（IISER博帕尔数据科学与工程系多机器人自主性实验室）
University of Edinburgh（爱丁堡大学）；University of Oxford（牛津大学）
Haptic interaction is essential for the dynamic dexterity of animals, which seamlessly switch from an impedance to an admittance behaviour using the force feedback from their proprioception. However, this ability is extremely challenging to reproduce in robots, especially when dealing with complex interaction dynamics, distributed contacts, and contact switching. Current model-based controllers require accurate interaction modelling to account for contacts and stabilise the interaction. In this manuscript, we propose an adaptive force/position controller that exploits the fractal impedance con…
Many high precision (dis)assembly tasks are still being performed by humans, whereas this is an ideal opportunity for automation. This paper provides a framework which enables a non-expert human operator to teach a robotic arm to do complex precision tasks. The framework uses a variable Cartesian impedance controller to execute trajectories learned from kinesthetic human demonstrations. Feedback can be given to interactively reshape or speed up the original demonstration. Board localization is done through a visual estimation of the task board position and refined through haptic feedback. Our …
University of Edinburgh（爱丁堡大学）；University of Oxford（牛津大学）
Path planning and collision avoidance are challenging in complex and highly variable environments due to the limited horizon of events. In literature, there are multiple model- and learning-based approaches that require significant computational resources to be effectively deployed and they may have limited generality. We propose a planning algorithm based on a globally stable passive controller that can plan smooth trajectories using limited computational resources in challenging environmental conditions. The architecture combines the recently proposed fractal impedance controller with elasti…
Interactive Motion Planning for Human-Robot Collaboration Based on Human-Centric Configuration Space Ergonomic Field
Department of Mechanical and Automation Engineering, T-Stone Robotics Institute, The Chinese University of Hong Kong（机械与自动化工程系，T-Stone机器人研究所，香港中文大学）；Idiap Research Institute（Idiap研究所）；Department of Advanced Robotics, Istituto Italiano di Tecnologia（先进机器人系，意大利Istituto Italiano di Tecnologia）
Humanoid robots are increasingly demanded to operate in interactive and human-surrounded environments while achieving sophisticated locomotion and manipulation tasks. To accomplish these tasks, roboticists unremittingly seek for advanced methods that generate whole-body coordination behaviors and meanwhile fulfill various planning and control objectives. Undoubtedly, these goals pose fundamental challenges to the robotics and control community. To take an incremental step towards reducing the performance gap between theoretical foundations and real implementations, we present a planning and co…
Unidirectional Human-Robot-Human Physical Interaction for Gait Training
The Biorobotics Institute, Scuola Superiore Sant’Anna（圣安娜高等学校生物机器人研究所）；Department of Excellence in Robotics & AI, Scuola Superiore Sant’Anna（圣安娜高等学校机器人与人工智能卓越系）；Shirley Ryan AbilityLab（雪莉·瑞安能力实验室）；Center for Robotics and Biosystems of Northwestern University（西北大学机器人与生物系统中心）；Department of Biomedical Engineering, Northwestern University（西北大学生物医学工程系）；Department of Physical Medicine and Rehabilitation, Northwestern University（西北大学物理医学与康复系）
UK National Centre for Nuclear Robotics（英国国家核机器人中心）；University of Birmingham（伯明翰大学）；National Nuclear Laboratory（国家核实验室）；University of West England（西英格兰大学）
This paper presents a method for constrained motion planning from vision, which enables a robot to move its end-effector over an observed surface, given start and destination points. The robot has no prior knowledge of the surface shape, but observes it from a noisy point-cloud camera. We consider the multi-objective optimisation problem of finding robot trajectories which maximise the robot's manipulability throughout the motion, while also minimising surface-distance travelled between the two points. This work has application in industrial problems of \textit{rough} robotic cutting, \textit{…
