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\n\n \n \n \n \n \n Modeling and Control of Sampled-Data Image-Based Visual Servoing With Three-Dimensional Features.\n \n \n \n\n\n \n Marco Costanzo; Giuseppe De Maria; Ciro Natale; and Antonio Russo.\n\n\n \n\n\n\n
IEEE Transactions on Control Systems Technology, 32(1): 31-46. 2024.\n
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@ARTICLE{Costanzo24_TCST,\n author={Costanzo, Marco and De Maria, Giuseppe and Natale, Ciro and Russo, Antonio},\n journal={IEEE Transactions on Control Systems Technology}, \n title={Modeling and Control of Sampled-Data Image-Based Visual Servoing With Three-Dimensional Features}, \n year={2024},\n volume={32},\n number={1},\n pages={31-46},\n keywords={Cameras;Visual servoing;Robots;Feature extraction;Asymptotic stability;Nonlinear systems;Algorithm design and analysis;Sampled-data control;stability of nonlinear systems;visual servo control},\n doi={10.1109/TCST.2023.3292311}\n}\n\n\n%%======================== book chapters\n\n\n
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\n\n \n \n \n \n \n \n Non-Prehensile Manipulation Actions and Visual 6D Pose Estimation for Fruit Grasping Based on Tactile Sensing.\n \n \n \n \n\n\n \n Marco Costanzo; Marco De Simone; Sara Federico; and Ciro Natale.\n\n\n \n\n\n\n
Robotics, 12(4): 92. Jun 2023.\n
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\n\n \n \n ![\"Non-Prehensile](\"//bibbase.org/img/filetypes/link.svg\"\n\t "\\"Paper\\"\n\t")
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@article{Costanzo23_MDPI_Robotics, \ntitle={Non-Prehensile Manipulation Actions and Visual 6D Pose Estimation for Fruit Grasping Based on Tactile Sensing}, \nvolume={12}, \nISSN={2218-6581}, \nurl={http://dx.doi.org/10.3390/robotics12040092}, \nDOI={10.3390/robotics12040092}, \nnumber={4}, \njournal={Robotics}, \npublisher={MDPI AG}, \nauthor={Costanzo, Marco and De Simone, Marco and Federico, Sara and Natale, Ciro}, \nyear={2023}, \nmonth={Jun}, \npages={92} \n}\n\n\n
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\n\n \n \n \n \n \n \n Detecting and Controlling Slip through Estimation and Control of the Sliding Velocity.\n \n \n \n \n\n\n \n Marco Costanzo; Giuseppe De Maria; and Ciro Natale.\n\n\n \n\n\n\n
Applied Sciences, 13(2): 921. Jan 2023.\n
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@article{Costanzo23_MDPI_ApplSci, \ntitle={Detecting and Controlling Slip through Estimation and Control of the Sliding Velocity}, \nvolume={13}, \nISSN={2076-3417}, \nurl={http://dx.doi.org/10.3390/app13020921}, \nDOI={10.3390/app13020921}, \nnumber={2}, \njournal={Applied Sciences}, \npublisher={MDPI AG}, \nauthor={Costanzo, Marco and De Maria, Giuseppe and Natale, Ciro}, \nyear={2023}, \nmonth={Jan},\npages={921} }\n\n\n
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\n\n \n \n \n \n \n Stability and Convergence Analysis of 3D Feature-Based Visual Servoing.\n \n \n \n\n\n \n Marco Costanzo; Giuseppe De Maria; Ciro Natale; and Antonio Russo.\n\n\n \n\n\n\n
IEEE Robotics and Automation Letters, 7(4): 12022-12029. 2022.\n
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@ARTICLE{Costanzo22_RAL_VS,\n author={Costanzo, Marco and De Maria, Giuseppe and Natale, Ciro and Russo, Antonio},\n journal={IEEE Robotics and Automation Letters}, \n title={Stability and Convergence Analysis of 3D Feature-Based Visual Servoing}, \n year={2022},\n volume={7},\n number={4},\n pages={12022-12029},\n doi={10.1109/LRA.2022.3211154}}\n\n\n
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\n\n \n \n \n \n \n Tactile Feedback Enabling In-Hand Pivoting and Internal Force Control for Dual-Arm Cooperative Object Carrying.\n \n \n \n\n\n \n Marco Costanzo; Giuseppe De Maria; and Ciro Natale.\n\n\n \n\n\n\n
IEEE Robotics and Automation Letters, 7(4): 11466-11473. 2022.\n
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@ARTICLE{Costanzo22_RAL_dual_arm,\n author={Costanzo, Marco and De Maria, Giuseppe and Natale, Ciro},\n journal={IEEE Robotics and Automation Letters}, \n title={Tactile Feedback Enabling In-Hand Pivoting and Internal Force Control for Dual-Arm Cooperative Object Carrying}, \n year={2022},\n volume={7},\n number={4},\n pages={11466-11473},\n doi={10.1109/LRA.2022.3202358}}\n\n \n
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\n\n \n \n \n \n \n A Multimodal Approach to Human Safety in Collaborative Robotic Workcells.\n \n \n \n\n\n \n Marco Costanzo; Giuseppe De Maria; Gaetano Lettera; and Ciro Natale.\n\n\n \n\n\n\n
IEEE Transactions on Automation Science and Engineering, 19(2): 1202-1216. 2022.\n
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@ARTICLE{Costanzo21_TASE,\n author={Costanzo, Marco and De Maria, Giuseppe and Lettera, Gaetano and Natale, Ciro},\n journal={IEEE Transactions on Automation Science and Engineering}, \n title={A Multimodal Approach to Human Safety in Collaborative Robotic Workcells}, \n year={2022},\n volume={19},\n number={2},\n pages={1202-1216},\n keywords={Robots;Safety;Collaboration;Robot sensing systems;Service robots;Collision avoidance;Cameras;Convolutional neural network (CNN);fuzzy control logic;human–robot collaboration (HRC);industrial robot;motion planning;multimodal perception system;safety standards;workspace monitoring},\n doi={10.1109/TASE.2020.3043286}\n}\n\n\n
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\n\n \n \n \n \n \n \n Handover Control for Human-Robot and Robot-Robot Collaboration.\n \n \n \n \n\n\n \n Marco Costanzo; Giuseppe De Maria; and Ciro Natale.\n\n\n \n\n\n\n
Frontiers in Robotics and AI, 8: 132. 2021.\n
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@ARTICLE{Costanzo21_Frontiers,\nAUTHOR={Costanzo, Marco and {De Maria}, Giuseppe and Natale, Ciro}, \nTITLE={Handover Control for Human-Robot and Robot-Robot Collaboration}, \nJOURNAL={Frontiers in Robotics and AI}, \nVOLUME={8}, \nPAGES={132}, \nYEAR={2021}, \nURL={https://www.frontiersin.org/article/10.3389/frobt.2021.672995}, \nDOI={10.3389/frobt.2021.672995}, \nISSN={2296-9144}, \nABSTRACT={Modern scenarios in robotics involve human-robot collaboration or robot-robot cooperation in unstructured environments. In human-robot collaboration, the objective is to relieve humans from repetitive and wearing tasks. This is the case of a retail store, where the robot could help a clerk to refill a shelf or an elderly customer to pick an item from an uncomfortable location. In robot-robot cooperation, automated logistics scenarios, such as warehouses, distribution centers and supermarkets, often require repetitive and sequential pick and place tasks that can be executed more efficiently by exchanging objects between robots, provided that they are endowed with object handover ability. Use of a robot for passing objects is justified only if the handover operation is sufficiently intuitive for the involved humans, fluid and natural, with a speed comparable to that typical of a human-human object exchange. The approach proposed in this paper strongly relies on visual and haptic perception combined with suitable algorithms for controlling both robot motion, to allow the robot to adapt to human behavior, and grip force, to ensure a safe handover. The control strategy combines model-based reactive control methods with an event-driven state machine encoding a human-inspired behavior during a handover task, which involves both linear and torsional loads, without requiring explicit learning from human demonstration. Experiments in a supermarket-like environment with humans and robots communicating only through haptic cues demonstrate the relevance of force/tactile feedback in accomplishing handover operations in a collaborative task.}\n}\n\n\n
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\n Modern scenarios in robotics involve human-robot collaboration or robot-robot cooperation in unstructured environments. In human-robot collaboration, the objective is to relieve humans from repetitive and wearing tasks. This is the case of a retail store, where the robot could help a clerk to refill a shelf or an elderly customer to pick an item from an uncomfortable location. In robot-robot cooperation, automated logistics scenarios, such as warehouses, distribution centers and supermarkets, often require repetitive and sequential pick and place tasks that can be executed more efficiently by exchanging objects between robots, provided that they are endowed with object handover ability. Use of a robot for passing objects is justified only if the handover operation is sufficiently intuitive for the involved humans, fluid and natural, with a speed comparable to that typical of a human-human object exchange. The approach proposed in this paper strongly relies on visual and haptic perception combined with suitable algorithms for controlling both robot motion, to allow the robot to adapt to human behavior, and grip force, to ensure a safe handover. The control strategy combines model-based reactive control methods with an event-driven state machine encoding a human-inspired behavior during a handover task, which involves both linear and torsional loads, without requiring explicit learning from human demonstration. Experiments in a supermarket-like environment with humans and robots communicating only through haptic cues demonstrate the relevance of force/tactile feedback in accomplishing handover operations in a collaborative task.\n
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\n\n \n \n \n \n \n Optical Force/Tactile Sensors for Robotic Applications.\n \n \n \n\n\n \n Marco Costanzo; and Salvatore Pirozzi.\n\n\n \n\n\n\n
IEEE Instrumentation Measurement Magazine, 24(5): 28-35. 2021.\n
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@ARTICLE{Costanzo21_Measurement_Magazine,\n author={Costanzo, Marco and Pirozzi, Salvatore},\n journal={IEEE Instrumentation Measurement Magazine}, \n title={Optical Force/Tactile Sensors for Robotic Applications}, \n year={2021},\n volume={24},\n number={5},\n pages={28-35},\n doi={10.1109/MIM.2021.9491003}\n}\n \n\n
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\n\n \n \n \n \n \n \n Control of robotic object pivoting based on tactile sensing.\n \n \n \n \n\n\n \n Marco Costanzo.\n\n\n \n\n\n\n
Mechatronics, 76: 102545. 2021.\n
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@article{Costanzo21_Mechatronics,\ntitle = {Control of robotic object pivoting based on tactile sensing},\njournal = {Mechatronics},\nvolume = {76},\npages = {102545},\nyear = {2021},\nissn = {0957-4158},\ndoi = {https://doi.org/10.1016/j.mechatronics.2021.102545},\nurl = {https://www.sciencedirect.com/science/article/pii/S095741582100043X},\nauthor = {Marco Costanzo},\nkeywords = {Robotic manipulators, Robot control, Friction, Nonlinear systems, Observers},\nabstract = {Robotic manipulation of objects using the sole tactile feedback is a challenge. If the contact between the robot end effector and the manipulated object is distributed, the robot can exchange both friction forces and torques with it. The friction highly influences the motion of the object. By controlling the friction it is possible to perform complex manipulation tasks, such as moving the object with respect to the end effector by executing a controlled sliding motion. If the motion is a rotation with respect to the end effector, the corresponding maneuver is called pivoting. Control of the pivoting motion is considerably difficult, especially without any visual feedback. This paper proposes a novel method to regulate the object angular position, by means of a pivoting maneuver, through a parallel gripper endowed with force/tactile sensors. The strategy is based on a novel nonlinear observer that estimates the sliding velocity from force/torque measurements and a model of the sliding dynamics. We exploit the Limit Surface concept and the LuGre friction model to build a dynamic model of a planar slider. We show, through experimental results, that simple parallel grippers are able to execute such maneuvers that correspond to adding a virtual joint between the fingers, thus enlarging the robot workspace.}\n}\n\n\n
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\n Robotic manipulation of objects using the sole tactile feedback is a challenge. If the contact between the robot end effector and the manipulated object is distributed, the robot can exchange both friction forces and torques with it. The friction highly influences the motion of the object. By controlling the friction it is possible to perform complex manipulation tasks, such as moving the object with respect to the end effector by executing a controlled sliding motion. If the motion is a rotation with respect to the end effector, the corresponding maneuver is called pivoting. Control of the pivoting motion is considerably difficult, especially without any visual feedback. This paper proposes a novel method to regulate the object angular position, by means of a pivoting maneuver, through a parallel gripper endowed with force/tactile sensors. The strategy is based on a novel nonlinear observer that estimates the sliding velocity from force/torque measurements and a model of the sliding dynamics. We exploit the Limit Surface concept and the LuGre friction model to build a dynamic model of a planar slider. We show, through experimental results, that simple parallel grippers are able to execute such maneuvers that correspond to adding a virtual joint between the fingers, thus enlarging the robot workspace.\n
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\n\n \n \n \n \n \n Can Robots Refill a Supermarket Shelf?: Motion Planning and Grasp Control.\n \n \n \n\n\n \n Marco Costanzo; Giuseppe De Maria; Gaetano Lettera; and Ciro Natale.\n\n\n \n\n\n\n
IEEE Robotics & Automation Magazine, 28(2): 61-73. 2021.\n
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@ARTICLE{Costanzo21_RAM,\n author={Costanzo, Marco and De Maria, Giuseppe and Lettera, Gaetano and Natale, Ciro},\n journal={IEEE Robotics \\& Automation Magazine}, \n title={Can Robots Refill a Supermarket Shelf?: Motion Planning and Grasp Control}, \n year={2021},\n volume={28},\n number={2},\n pages={61-73},\n keywords={Robots;Market research;Task analysis;Grippers;Grasping;Cameras;Automation;Warehousing;Production facilities;Storage automation},\n doi={10.1109/MRA.2021.3064754}\n}\n\n\n
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\n\n \n \n \n \n \n \n Tactile Sensors for Parallel Grippers: Design and Characterization.\n \n \n \n \n\n\n \n Andrea Cirillo; Marco Costanzo; Gianluca Laudante; and Salvatore Pirozzi.\n\n\n \n\n\n\n
Sensors, 21(5). 2021.\n
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@Article{Cirillo21_Sensors,\nAUTHOR = {Cirillo, Andrea and Costanzo, Marco and Laudante, Gianluca and Pirozzi, Salvatore},\nTITLE = {Tactile Sensors for Parallel Grippers: Design and Characterization},\nJOURNAL = {Sensors},\nVOLUME = {21},\nYEAR = {2021},\nNUMBER = {5},\nARTICLE-NUMBER = {1915},\nURL = {https://www.mdpi.com/1424-8220/21/5/1915},\nISSN = {1424-8220},\nABSTRACT = {Tactile data perception is of paramount importance in today’s robotics applications. This paper describes the latest design of the tactile sensor developed in our laboratory. Both the hardware and firmware concepts are reported in detail in order to allow the research community the sensor reproduction, also according to their needs. The sensor is based on optoelectronic technology and the pad shape can be adapted to various robotics applications. A flat surface, as the one proposed in this paper, can be well exploited if the object sizes are smaller than the pad and/or the shape recognition is needed, while a domed pad can be used to manipulate bigger objects. Compared to the previous version, the novel tactile sensor has a larger sensing area and a more robust electronic, mechanical and software design that yields less noise and higher flexibility. The proposed design exploits standard PCB manufacturing processes and advanced but now commercial 3D printing processes for the realization of all components. A GitHub repository has been prepared with all files needed to allow the reproduction of the sensor for the interested reader. The whole sensor has been tested with a maximum load equal to 15N, by showing a sensitivity equal to 0.018V/N. Moreover, a complete and detailed characterization for the single taxel and the whole pad is reported to show the potentialities of the sensor also in terms of response time, repeatability, hysteresis and signal to noise ratio.},\nDOI = {10.3390/s21051915}\n}\n\n\n
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\n Tactile data perception is of paramount importance in today’s robotics applications. This paper describes the latest design of the tactile sensor developed in our laboratory. Both the hardware and firmware concepts are reported in detail in order to allow the research community the sensor reproduction, also according to their needs. The sensor is based on optoelectronic technology and the pad shape can be adapted to various robotics applications. A flat surface, as the one proposed in this paper, can be well exploited if the object sizes are smaller than the pad and/or the shape recognition is needed, while a domed pad can be used to manipulate bigger objects. Compared to the previous version, the novel tactile sensor has a larger sensing area and a more robust electronic, mechanical and software design that yields less noise and higher flexibility. The proposed design exploits standard PCB manufacturing processes and advanced but now commercial 3D printing processes for the realization of all components. A GitHub repository has been prepared with all files needed to allow the reproduction of the sensor for the interested reader. The whole sensor has been tested with a maximum load equal to 15N, by showing a sensitivity equal to 0.018V/N. Moreover, a complete and detailed characterization for the single taxel and the whole pad is reported to show the potentialities of the sensor also in terms of response time, repeatability, hysteresis and signal to noise ratio.\n
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\n\n \n \n \n \n \n \n Modeling and slipping control of a planar slider.\n \n \n \n \n\n\n \n Alberto Cavallo; Marco Costanzo; Giuseppe De Maria; and Ciro Natale.\n\n\n \n\n\n\n
Automatica, 115: 108875. 2020.\n
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@article{CAVALLO20_Automatica,\ntitle = "Modeling and slipping control of a planar slider",\njournal = "Automatica",\nvolume = "115",\npages = "108875",\nyear = "2020",\nissn = "0005-1098",\ndoi = "https://doi.org/10.1016/j.automatica.2020.108875",\nurl = "http://www.sciencedirect.com/science/article/pii/S000510982030073X",\nauthor = "Alberto Cavallo and Marco Costanzo and Giuseppe De Maria and Ciro Natale",\nkeywords = "Friction, Lyapunov stability, Robotic manipulators, Force control, Nonlinear systems",\nabstract = "The paper presents a novel strategy to control the instantaneous rotational velocity of a planar slider subject to a soft contact with friction and to external loads, including gravity. The approach is based on a novel model that combines the LuGre dynamic friction model with the limit surface concept for two main reasons. First, the limit surface allows considering both translational and rotational sliding motions. Secondly, the actual friction provided at the contact by the LuGre dynamic model exhibits dependence on the rate of variation of the external loads and, thus, it is worthwhile in dynamic conditions. Slipping control is realized by acting on the friction forces through the normal load so as to stably regulate the velocity of the slider to zero. The control law exploits a nonlinear observer, based on the proposed model, to estimate the instantaneous rotational velocity of the slider, which is used to compute the normal load necessary to ensure a globally asymptotically stable equilibrium of the slider. Experimental results show the effectiveness of the approach in an application of robotic manipulation using an industrial gripper sensorized with force/tactile sensors."\n}\n\n\n
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\n The paper presents a novel strategy to control the instantaneous rotational velocity of a planar slider subject to a soft contact with friction and to external loads, including gravity. The approach is based on a novel model that combines the LuGre dynamic friction model with the limit surface concept for two main reasons. First, the limit surface allows considering both translational and rotational sliding motions. Secondly, the actual friction provided at the contact by the LuGre dynamic model exhibits dependence on the rate of variation of the external loads and, thus, it is worthwhile in dynamic conditions. Slipping control is realized by acting on the friction forces through the normal load so as to stably regulate the velocity of the slider to zero. The control law exploits a nonlinear observer, based on the proposed model, to estimate the instantaneous rotational velocity of the slider, which is used to compute the normal load necessary to ensure a globally asymptotically stable equilibrium of the slider. Experimental results show the effectiveness of the approach in an application of robotic manipulation using an industrial gripper sensorized with force/tactile sensors.\n
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\n\n \n \n \n \n \n Manipulation Planning and Control for Shelf Replenishment.\n \n \n \n\n\n \n M. Costanzo; S. Stelter; C. Natale; S. Pirozzi; G. Bartels; A. Maldonado; and M. Beetz.\n\n\n \n\n\n\n
IEEE Robotics and Automation Letters, 5(2): 1595-1601. April 2020.\n
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@ARTICLE{Costanzo20_RAL,\n author={M. {Costanzo} and S. {Stelter} and C. {Natale} and S. {Pirozzi} and G. {Bartels} and A. {Maldonado} and M. {Beetz}},\n journal={IEEE Robotics and Automation Letters}, \n title={Manipulation Planning and Control for Shelf Replenishment}, \n year={2020},\n volume={5},\n number={2},\n pages={1595-1601},\n abstract={Manipulation planning and control are relevant building blocks of a robotic system and their tight integration is a key factor to improve robot autonomy and allows robots to perform manipulation tasks of increasing complexity, such as those needed in the in-store logistics domain. Supermarkets contain a large variety of objects to be placed on the shelf layers with specific constraints, doing this with a robot is a challenge and requires a high dexterity. However, an integration of reactive grasping control and motion planning can allow robots to perform such tasks even with grippers with limited dexterity. The main contribution of the letter is a novel method for planning manipulation tasks to be executed using a reactive control layer that provides more control modalities, i.e., slipping avoidance and controlled sliding. Experiments with a new force/tactile sensor equipping the gripper of a mobile manipulator show that the approach allows the robot to successfully perform manipulation tasks unfeasible with a standard fixed grasp.},\n keywords={dexterous manipulators;grippers;logistics;manipulator dynamics;mobile robots;path planning;tactile sensors;force sensor;tactile sensor;controlled sliding;slipping avoidance;grippers;robot autonomy;robotic system;relevant building blocks;shelf replenishment;manipulation planning;mobile manipulator;control modalities;reactive control layer;manipulation tasks;motion planning;reactive grasping control;high dexterity;shelf layers;in-store logistics domain;Robot sensing systems;Grippers;Task analysis;Force;Planning;Control systems;Motion and path planning;manipulation planning},\n doi={10.1109/LRA.2020.2969179},\n ISSN={2377-3766},\n month={April},}\n\n\n
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\n Manipulation planning and control are relevant building blocks of a robotic system and their tight integration is a key factor to improve robot autonomy and allows robots to perform manipulation tasks of increasing complexity, such as those needed in the in-store logistics domain. Supermarkets contain a large variety of objects to be placed on the shelf layers with specific constraints, doing this with a robot is a challenge and requires a high dexterity. However, an integration of reactive grasping control and motion planning can allow robots to perform such tasks even with grippers with limited dexterity. The main contribution of the letter is a novel method for planning manipulation tasks to be executed using a reactive control layer that provides more control modalities, i.e., slipping avoidance and controlled sliding. Experiments with a new force/tactile sensor equipping the gripper of a mobile manipulator show that the approach allows the robot to successfully perform manipulation tasks unfeasible with a standard fixed grasp.\n
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\n\n \n \n \n \n \n Two-Fingered In-Hand Object Handling Based on Force/Tactile Feedback.\n \n \n \n\n\n \n M. Costanzo; G. De Maria; and C. Natale.\n\n\n \n\n\n\n
IEEE Transactions on Robotics, 36(1): 157-173. Feb 2020.\n
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@ARTICLE{Costanzo20_TRO,\n author={M. {Costanzo} and G. {De Maria} and C. {Natale}},\n journal={IEEE Transactions on Robotics}, \n title={Two-Fingered In-Hand Object Handling Based on Force/Tactile Feedback}, \n year={2020},\n volume={36},\n number={1},\n pages={157-173},\n abstract={This article describes a set of control algorithms for in-hand object handling using a parallel jaw gripper equipped with force/tactile sensors. The control strategy is model based and relies upon the limit surface concept. The LuGre friction model is combined with the limit surface method to set up a dynamic model of soft contact. The model is exploited to estimate the relative velocity of the object with respect to the fingers, so as to control the grip force to counteract possible slipping events due to external disturbances. Force/tactile feedback, the only perception source used by the algorithms, is suitably exploited not only for safe grasping of a variety of objects with uncertain weight and inertial properties, but also for in-hand manipulation actions, like object pivoting or gripper pivoting. Since the algorithm is based on the control of the object velocity, accuracy of the desired object positioning depends on the initial grasp configuration, as well as on the accuracy of the friction model parameters. Such manipulation skills are evaluated in the execution of various pick and place tasks typical of an in-store logistic scenario.},\n keywords={dexterous manipulators;feedback;force control;force sensors;friction;grippers;industrial manipulators;position control;tactile sensors;parallel jaw gripper;control strategy;limit surface concept;LuGre friction model;limit surface method;dynamic model;soft contact;relative velocity;grip force;slipping events;in-hand manipulation actions;object pivoting;object velocity;object positioning;friction model parameters;fingered in-hand object handling;Grippers;Force;Robot sensing systems;Dynamics;Task analysis;Contact modeling;dexterous manipulation;force and tactile sensing;sensor-based control},\n doi={10.1109/TRO.2019.2944130},\n ISSN={1941-0468},\n month={Feb},}\n\n\n
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\n This article describes a set of control algorithms for in-hand object handling using a parallel jaw gripper equipped with force/tactile sensors. The control strategy is model based and relies upon the limit surface concept. The LuGre friction model is combined with the limit surface method to set up a dynamic model of soft contact. The model is exploited to estimate the relative velocity of the object with respect to the fingers, so as to control the grip force to counteract possible slipping events due to external disturbances. Force/tactile feedback, the only perception source used by the algorithms, is suitably exploited not only for safe grasping of a variety of objects with uncertain weight and inertial properties, but also for in-hand manipulation actions, like object pivoting or gripper pivoting. Since the algorithm is based on the control of the object velocity, accuracy of the desired object positioning depends on the initial grasp configuration, as well as on the accuracy of the friction model parameters. Such manipulation skills are evaluated in the execution of various pick and place tasks typical of an in-store logistic scenario.\n
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\n\n \n \n \n \n \n \n Design and Calibration of a Force/Tactile Sensor for Dexterous Manipulation.\n \n \n \n \n\n\n \n Marco Costanzo; Giuseppe De Maria; Ciro Natale; and Salvatore Pirozzi.\n\n\n \n\n\n\n
Sensors, 19(4): 966. Feb 2019.\n
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@article{Costanzo19_MDPI_AG_Sensors, \ntitle={Design and Calibration of a Force/Tactile Sensor for Dexterous Manipulation}, \nvolume={19}, \nISSN={1424-8220}, \nurl={http://dx.doi.org/10.3390/s19040966}, \nDOI={10.3390/s19040966}, \nnumber={4}, \njournal={Sensors}, \npublisher={MDPI AG}, \nauthor={Costanzo, Marco and De Maria, Giuseppe and Natale, Ciro and Pirozzi, Salvatore}, \nyear={2019}, \nmonth={Feb}, \npages={966}\n}\n\n\n
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\n\n \n \n \n \n \n \n Motion Planning and Reactive Control Algorithms for Object Manipulation in Uncertain Conditions.\n \n \n \n \n\n\n \n Marco Costanzo; Giuseppe De Maria; Gaetano Lettera; Ciro Natale; and Salvatore Pirozzi.\n\n\n \n\n\n\n
Robotics, 7(4): 76. Nov 2018.\n
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@article{Costanzo18_MDPI_AG_Robotics, \ntitle={Motion Planning and Reactive Control Algorithms for Object Manipulation in Uncertain Conditions}, \nvolume={7}, \nISSN={2218-6581}, \nurl={http://dx.doi.org/10.3390/robotics7040076}, \nDOI={10.3390/robotics7040076}, \nnumber={4}, \njournal={Robotics}, \npublisher={MDPI AG}, \nauthor={Costanzo, Marco and De Maria, Giuseppe and Lettera, Gaetano and Natale, Ciro and Pirozzi, Salvatore}, \nyear={2018}, \nmonth={Nov}, \npages={76}\n}\n\n\n
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