Concept

Motion control

Related publications (144)

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

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 ...

EPFL2024

Passive Obstacle Aware Control to Follow Desired Velocity

Aude Billard, Lukas Huber

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 ...

2024

Robot Learning using Tensor Networks

Suhan Narayana Shetty

In various robotics applications, the selection of function approximation methods greatly influences the feasibility and computational efficiency of algorithms. Tensor Networks (TNs), also referred to as tensor decomposition techniques, present a versatile ...

EPFL2024

Targeted worker removal reveals a lack of flexibility in brood transport specialisation with no compensatory gain in efficiency

Mahmut Selman Sakar, Laurent Keller, Fazil Emre Uslu

Division of labour is widely thought to increase the task efficiency of eusocial insects. Workers can switch their task to compensate for sudden changes in demand, providing flexible task allocation. In combination with automated tracking technology, we de ...

2024

Morphological and Material Programability of a Hall-Effect Based Soft Tactile Sensors

Josephine Anna Eleanor Hughes, Sudong Lee

The different receptors in human skin show not only diversity in the stimuli to which they respond, but also variable sensitivity and directionality. This is often determined by their location or morphology, and can play an important role in filtering or a ...

IEEE2024

Mean Field Type Control With Species Dependent Dynamics via Structured Tensor Optimization

Isabel Haasler, Axel Ringh, Yiqiang Chen

In this letter we consider mean field type control problems with multiple species that have different dynamics. We formulate the discretized problem using a new type of entropy-regularized multimarginal optimal transport problems where the cost is a decomp ...

2023

Reinforcement learning for scaffold-free construction of spanning-structures

Maryam Kamgarpour, Stefana Parascho, Gabriel Rémi Vallat, Anna Maria Maddux, Jingwen Wang

In construction robotics, a conventional design-to-fabrication work-flow starts with designing a structure, followed by task and robotic motion planning, and ultimately, fabrication. However, this approach can prove unsuccessful, as we may only discover th ...

2023

Inverse Reinforcement Learning of Pedestrian-Robot Coordination

Aude Billard, David Julian Gonon

We apply inverse reinforcement learning (IRL) with a novel cost feature to the problem of robot navigation in human crowds. Consistent with prior empirical work on pedestrian behavior, the feature anticipates collisions between agents. We efficiently learn ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Dynamic control of high-voltage actuator arrays by light-pattern projection on photoconductive switches

Herbert Shea, Amir Firouzeh, Edouard Franck Vincent Gustave Leroy, Vesna Bacheva, Aiste Balciunaite

The ability to control high-voltage actuator arrays relies, to date, on expensive microelectronic processes or on individual wiring of each actuator to a single off-chip high-voltage switch. Here we present an alternative approach that uses on-chip photoco ...

SPRINGERNATURE2023

Bimanual dynamic grabbing and tossing of objects onto a moving target

Aude Billard, Michael Bosongo Bombile

Bimanual grabbing and tossing of packages onto trays or conveyor belts remains a human activity in the industry. For robots, such a dynamic task requires coordination between two arms and fast adaptation abilities when the tossing target is moving and subj ...

2023

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