Publication

Variable Duration Movement Encoding with Minimal Intervention Control

Publications associées (45)

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Evaluating and updating the obstacle avoidance velocity for an autonomous robot in real-time ensures robustness against noise and disturbances. A passive damping controller can obtain the desired motion with a torque-controlled robot, which remains complia ...

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Exact Obstacle Avoidance for Robots in Complex and Dynamic Environments Using Local Modulation

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Robots outside of the fenced factories have to deal with continuously changing environment, this requires fast and flexible modes of control. Planning methods or complex learning models can find optimal paths in complex surroundings, but they are computati ...

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A geometric optimal control approach for imitation and generalization of manipulation skills

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Daily manipulation tasks are characterized by regular features associated with the task structure, which can be described by multiple geometric primitives related to actions and object shapes. Only using Cartesian coordinate systems cannot fully represent ...

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Navigation of Concentric Tube Continuum Robots using Optimal Control

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Recently developed Concentric Tube Continuum Robots (CTCRs) are widely exploited in, for example in minimally invasive surgeries which involve navigating inside narrow body cavities close to sensitive regions. These CTCRs can be controlled by extending and ...

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We present drozBot: le robot portraitiste, a robotic system that draws artistic portraits of people. The input images for the portrait are taken interactively by the robot itself. We formulate the problem of drawing portraits as a problem of coverage which ...

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Implicit Distance Functions: Learning and Applications in Control

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Learning from demonstration using products of experts: Applications to manipulation and task prioritization

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Probability distributions are key components of many learning from demonstration (LfD) approaches, with the spaces chosen to represent tasks playing a central role. Although the robot configuration is defined by its joint angles, end-effector poses are oft ...

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Product of experts for robot learning from demonstration

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Adaptability and ease of programming are key features necessary for a wider spread of robotics in factories and everyday assistance. Learning from demonstration (LfD) is an approach to address this problem. It aims to develop algorithms and interfaces such ...

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This paper presents the first successful experiment implementing whole-body model predictive control with state feedback on a torque-control humanoid robot. We demonstrate that our control scheme is able to do whole-body target tracking, control the balanc ...

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Probabilistic Adaptive Control for Robust Behavior Imitation

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In the context of learning from demonstration (LfD), trajectory policy representations such as probabilistic movement primitives (ProMPs) allow for rich modeling of demonstrated skills. To reproduce a learned skill with a real robot, a feedback controller ...

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