Uploaded February 2021 | Updated September 2026, 2 weeks ago
https://www.ri.cmu.edu/event/ri-seminar-alberto-rodriguez-mit-associate-professor-2021-02-19/
The Role of Manipulation Primitives in Building Dexterous Robotic Systems
Alberto Rodriguez
Associate Professor
Mechanical Engineering, MIT
Abstract: I will start this talk by illustrating four different perspectives that we as a community have embraced to study robotic manipulation: 1) controlling a simplified model of the mechanics of interaction with an object; 2) using haptic feedback such as force or tactile to control the interaction with an environment; 3) planning sequences or trajectories of manipulation actions to achieve long-horizon goals; and 4) using visual cues to guide manipulation actions. These are complementary perspectives, and building general dexterous robotic manipulation systems requires integrating them. I will discuss the key role that manipulation primitives play at integrating these perspectives. In particular I will present recent work on tactile dexterity to embed tactile feedback into the mechanics models of frictional contact, and on planning with visual affordances to execute dexterous long-term behavior on novel objects. I will illustrate this work in the context of a dual-arm dexterous robotic system.
Brief Bio: Alberto Rodriguez is the Class of 1957 Associate Professor at the Mechanical Engineering Department at MIT. Alberto graduated in Mathematics (’05) and Telecommunication Engineering (’06) from the Universitat Politecnica de Catalunya, and earned his PhD (’13) from the Robotics Institute at Carnegie Mellon University. He leads the Manipulation and Mechanisms Lab at MIT (MCube) researching autonomous dexterous manipulation, and robot automation. Alberto has received Best Paper Awards at conferences RSS’11, ICRA’13, RSS’18, IROS’18, and RSS’19, the 2018 Best Manipulation System Paper Award from Amazon, and has been finalist for best paper awards at IROS’16, IROS’18, ICRA’20 and RSS’20. He has led Team MIT-Princeton in the Amazon Robotics Challenge between 2015 and 2017, and has received Faculty Research Awards from Amazon in 2018, 2019 and 2020, and from Google in 2020. He is also the recipient of the 2020 IEEE Early Academic Career Award in Robotics and Automation.
https://www.ri.cmu.edu/event/ri-seminar-alberto-rodriguez-mit-associate-professor-2021-02-19/
The Role of Manipulation Primitives in Building Dexterous Robotic Systems
Alberto Rodriguez
Associate Professor
Mechanical Engineering, MIT
Abstract: I will start this talk by illustrating four different perspectives that we as a community have embraced to study robotic manipulation: 1) controlling a simplified model of the mechanics of interaction with an object; 2) using haptic feedback such as force or tactile to control the interaction with an environment; 3) planning sequences or trajectories of manipulation actions to achieve long-horizon goals; and 4) using visual cues to guide manipulation actions. These are complementary perspectives, and building general dexterous robotic manipulation systems requires integrating them. I will discuss the key role that manipulation primitives play at integrating these perspectives. In particular I will present recent work on tactile dexterity to embed tactile feedback into the mechanics models of frictional contact, and on planning with visual affordances to execute dexterous long-term behavior on novel objects. I will illustrate this work in the context of a dual-arm dexterous robotic system.
Brief Bio: Alberto Rodriguez is the Class of 1957 Associate Professor at the Mechanical Engineering Department at MIT. Alberto graduated in Mathematics (’05) and Telecommunication Engineering (’06) from the Universitat Politecnica de Catalunya, and earned his PhD (’13) from the Robotics Institute at Carnegie Mellon University. He leads the Manipulation and Mechanisms Lab at MIT (MCube) researching autonomous dexterous manipulation, and robot automation. Alberto has received Best Paper Awards at conferences RSS’11, ICRA’13, RSS’18, IROS’18, and RSS’19, the 2018 Best Manipulation System Paper Award from Amazon, and has been finalist for best paper awards at IROS’16, IROS’18, ICRA’20 and RSS’20. He has led Team MIT-Princeton in the Amazon Robotics Challenge between 2015 and 2017, and has received Faculty Research Awards from Amazon in 2018, 2019 and 2020, and from Google in 2020. He is also the recipient of the 2020 IEEE Early Academic Career Award in Robotics and Automation.
