Publications associées à Cheetah-cub-S: Steering of a Quadruped Robot using Trunk Motion

Online Multicontact Receding Horizon Planning via Value Function Approximation

Planning multicontact motions in a receding horizon fashion requires a value function to guide the planning with respect to the future, e.g., building momentum to traverse large obstacles. Traditionally, the value function is approximated by computing traj ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Investigating neural resource allocation in the sensorimotor control of extra limbs

Giulia Dominijanni

The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

EPFL2024

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

Lukas Huber

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

Memento Mori: Reliable robustness in self-reconfigurable modular robots

Kevin Andrew Holdcroft

Modular robotics link the reliability of a centralised system with the adaptivity of a decentralised system. It is difficult for a robot with a fixed shape to be able to perform many different types of tasks. As the task space grows, the number of functi ...

EPFL2024

Sense in Motion with Belief Clustering: Efficient Gas Source Localization with Mobile Robots

Alcherio Martinoli, Wanting Jin

Given the patchy nature of gas plumes and the slow response of conventional gas sensors, the use of mobile robots for Gas Source Localization (GSL) tasks presents significant challenges. These aspects increase the difficulties in obtaining gas measurements ...

2024

Hitting with Different Joints of a Robotic Manipulator

Aude Billard, Harshit Khurana

This paper builds up the skill of impact aware non prehensile manipulation through a hitting motion by allowing the robot arm to come in contact with the environment with parts other than its end effector. Hitting with other joints allows us to manipulate ...

2024

Distributed Predictive Formation Control of Autonomous Rotary-Wing Micro Aerial Vehicles

Izzet Kagan Erünsal

This doctoral thesis navigates the complex landscape of motion coordination and formation control within teams of rotary-wing Micro Aerial Vehicles (MAVs). Prompted by the intricate demands of real-world applications such as search and rescue or surveillan ...

EPFL2024

A Biohybrid Superorganism - Investigating honeybees' collective behaviors via interactive robotics

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Social insects, such as ants, termites, and honeybees, have evolved sophisticated societies where the collaborative efforts of "simple" individuals can lead to the emergence of complex dynamics. The reliance of each organism on the collective is so great t ...

EPFL2024

Puppeteer and Marionette: Learning Anticipatory Quadrupedal Locomotion Based on Interactions of a Central Pattern Generator and Supraspinal Drive

Auke Ijspeert, Milad Shafiee Ashtiani, Guillaume Denis Antoine Bellegarda

Quadruped animal locomotion emerges from the interactions between the spinal central pattern generator (CPG), sensory feedback, and supraspinal drive signals from the brain. Computational models of CPGs have been widely used for investigating the spinal co ...

IEEE2023

Exploration-based model learning with self-attention for risk-sensitive robot control

Sudong Lee

Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics ...

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Inferring individual evaluation criteria for reaching trajectories with obstacle avoidance from EEG signals

Aude Billard, José del Rocio Millán Ruiz, Fumiaki Iwane

During reaching actions, the human central nerve system (CNS) generates the trajectories that optimize effort and time. When there is an obstacle in the path, we make sure that our arm passes the obstacle with a sufficient margin. This comfort margin varie ...

Nature Portfolio2023

Haptics based collaborative steering control in automated driving environments

Tomohiro Nakade

A vehicle's steering is a particular system in that it is exposed to individual subjective reviews based on criteria that are hard to assess quantitatively. Haptic design of such systems is a prime concern that has been at the center of industrial developm ...

EPFL2023

Reinforcement learning for scaffold-free construction of spanning-structures

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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 ...

New York2023

Implicit Distance Functions: Learning and Applications in Robotics

Mikhail Koptev

In this thesis, we address the complex issue of collision avoidance in the joint space of robots. Avoiding collisions with both the robot's own body parts and obstacles in the environment is a critical constraint in motion planning and is crucial for ensur ...

EPFL2023

Self-Correcting Quadratic Programming-Based Robot Control

Aude Billard, Konstantinos Chatzilygeroudis, Farshad Khadivar

Quadratic Programming (QP)-based controllers allow many robotic systems, such as humanoids, to successfully undertake complex motions and interactions. However, these approaches rely heavily on adequately capturing the underlying model of the environment a ...

2023

Identifying important sensory feedback for learning locomotion skills

Auke Ijspeert, Milad Shafiee Ashtiani, Guillaume Denis Antoine Bellegarda

Robot motor skills can be acquired by deep reinforcement learning as neural networks to reflect state-action mapping. The selection of states has been demonstrated to be crucial for successful robot motor learning. However, because of the complexity of neu ...

NATURE PORTFOLIO2023

Motion Planning and Inertia Based Control for Impact Aware Manipulation

Aude Billard, Harshit Khurana

In this paper, we propose a metric called hitting flux which is used in the motion generation and controls for a robot manipulator to interact with the environment through a hitting or a striking motion. Given the task of placing a known object outside of ...

2023

Avian-Inspired Claws Enable Robot Perching or Walking

Dario Floreano, William John Stewart, Won Dong Shin, Mohammad Askari

Multimodal unmanned aerial vehicles (UAVs) are rarely capable of more than two modalities, i.e., flying and walking or flying and perching. However, being able to fly, perch, and walk could further improve their usefulness by expanding their operating enve ...

2023

Morphological flexibility in robotic systems through physical polygon meshing

Jamie Paik, Christoph Heinrich Belke, Kevin Andrew Holdcroft, Alexander Thomas Sigrist

Shape-changing robots adapt their own morphology to address a wider range of functions or environments than is possible with a fixed or rigid structure. Akin to biological organisms, the ability to alter shape or configuration emerges from the underlying m ...

Nature Portfolio2023

Multi-robot task allocation for safe planning against stochastic hazard dynamics

Orcun Karaca, Maryam Kamgarpour

We address multi-robot safe mission planning in uncertain dynamic environments. This problem arises in several applications including safety-critical exploration, surveillance, and emergency rescue missions. Computation of a multi-robot optimal control pol ...

IEEE2023