32 accepted papers
This work proposes a method for learning features from a batch of 2D sonar images to predict a multi-view point-cloud for achieving a dense 3D-reconstruction. In comparison to vision-based sensors, acoustics are considered a reliable sensing modality in underwater environments. The output of sonars …
In robotics many different approaches ranging from classical planning over optimal control to reinforcement learning (RL) are developed and borrowed from other fields to achieve reliable control in diverse tasks. In order to get a clear understanding of their individual strengths and weaknesses and …
Learning-based methods have enabled robots to acquire bio-inspired movements with increasing levels of naturalness and adaptability. Among these, Imitation Learning (IL) has proven effective in transferring complex motion patterns from animals to robotic systems. However, current state-of-the-art fr…
Many real-world applications require legged robots to be able to carry variable payloads. Model-Based controllers such as model predictive control (MPC) have become the de facto standard in research for controlling these systems. However, most model-based control architectures use fixed plant models
Quadratic Programs (QPs) are widely used in the control of walking robots, especially in Model Predictive Control (MPC) and Whole-Body Control (WBC). In both cases, the controller design requires the formulation of a QP and the selection of a suitable QP solver, both requiring considerable time and
In robotics, structural design and behavior optimization have long been considered separate processes, resulting in the development of systems with limited capabilities. Recently, co-design methods have gained popularity, where bi-level formulations are used to simultaneously optimize the robot desi
The employment of walking excavator robots, endowed with hybrid locomotion capabilities, holds considerable promise in facilitating the execution of intricate tasks in challenging terrain environments. A critical skill for such a system pertains to traversing obstacles through stepping locomotion, a
In this paper, we present an attitude control scheme for an autonomous underwater vehicle (AUV), which is based on incremental nonlinear dynamic inversion (INDI). Conventional model-based controllers depend on an exact model of the controlled system, which is difficult to find, especially for marine…
Exploration missions on extra terrestrial celestial bodies are to date performed by complex and heavy robotic systems. The trend is towards lighter modular systems that can be (re)configured in situ according to mission specific requirements. To facilitate flexible configurability, a multifunctional…
Reliable detection of human intentions from electroencephalogram (EEG) to improve human-robot interaction (HRI) has recently gained significant importance. To ensure safe and satisfactory interactions, implicit detection of erroneous behavior of robotic systems, particularly assistive devices, is es…
A great advantage of legged robots is their ability to operate on particularly difficult and obstructed terrain, which demands dynamic, robust, and precise movements. The study of obstacle courses provides invaluable insights into the challenges legged robots face, offering a controlled environment
As artificial intelligence gains new capabilities, it becomes important to evaluate it on real-world tasks. In particular, the fields of robotics and reinforcement learning (RL) are lacking in standardized benchmarking tasks on real hardware. To facilitate reproducibility and stimulate algorithmi…
This paper presents the design, analysis, and performance evaluation of RicMonk, a novel three-link brachiation robot equipped with passive hook-shaped grippers. Brachiation, an agile and energy-efficient mode of locomotion observed in primates, has inspired the development of RicMonk to explore ver…
Optimal behaviours of a system to perform a specific task can be achieved by leveraging the coupling between trajectory optimization, stabilization, and design optimization. This approach is particularly advantageous for underactuated systems, which are systems that have fewer actuators than degrees…
Brachiation is a dynamic, coordinated swinging maneuver of body and arms used by monkeys and apes to move between branches. As a unique underactuated mode of locomotion, it is interesting to study from a robotics perspective since it can broaden the deployment scenarios for humanoids and animaloids.
Legged locomotion is arguably the most suited and versatile mode to deal with natural or unstructured terrains. Intensive research into dynamic walking and running controllers has recently yielded great advances, both in the optimal control and reinforcement learning (RL) literature. Hopping is a ch…
Trajectory optimization methods have become ubiquitous for the motion planning and control of underactuated robots for e.g., quadrupeds, humanoids etc. While they have been extensively used in the case of serial or tree type robots, they are seldomly used for planning and control of robots with clos…
This work proposes the use of conditional Generative Adversarial Networks (cGANs) for acoustic-based 3D reconstruction. Acoustics being the most reliable sensor modality in underwater domains is accompanied with the loss of elevation angle in its images. The challenge of recovering the missing dimen…
Unlike fully actuated systems, the control of underactuated robots necessitates the use of passive dynamics to fulfill control objectives. Hence, there is an increased interdependence between their design parameters and the closed loop performance. This paper proposes a novel approach for co-optimiz…
It is well established that a stiff structure along with an optimal mass distribution are key features to perform dynamic movements, and parallel designs provide these characteristics to a robot. This work presents the new upper-body design of the humanoid robot RH5 named RH5 Manus with series-paral…
Modeling closed loop mechanisms is a necessity for the control and simulation of various systems and poses a great challenge to rigid body dynamics algorithms. Solving the forward and inverse dynamics for such systems require resolution of loop closure constraints which are often solved via numerica…
Musical dancing is an ubiquitous phenomenon in the human society. Providing robots the ability to dance has the potential to make the human robot co-existence more acceptable in our society. Hence, dancing robots have generated a considerable research interest in the recent years. In this paper, we…
Parallel mechanisms are becoming increasingly popular as subsystems in various robots due to their superior stiffness, payload-to-weight ratio, and dynamic properties. The serial connection of parallel subsystems leads to series-parallel hybrid robots, which are more difficult to model and control t…
Flexible adaptation of learning strategy depending on online changes of the user's current intents have a high relevance in human-robot collaboration. In our previous study, we proposed an intrinsic interactive reinforcement learning approach for human-robot interaction, in which a robot learns his/…
Learning the dynamics of robots from data can help achieve more accurate tracking controllers, or aid their navigation algorithms. However, when the actual dynamics of the robots change due to external conditions, on-line adaptation of their models is required to maintain high fidelity performance.…
It is becoming increasingly popular to use parallel mechanisms as modular subsystem units in the design of various robots for their superior stiffness, payload-to-weight ratio and dynamic properties. This leads to series-parallel hybrid robotic systems which pose several challenges in their modeling…
In this work we investigate the identification of a motion model for an autonomous underwater vehicle by applying different machine learning (ML) regression methods. By using the data collected from the robot's on-board navigation sensors, we train the regression models to learn the damping term whi…
Since early in robotics the performance of odometry techniques has been of constant research for mobile robots. This is due to its direct influence on localization. The pose error grows unbounded in dead-reckoning systems and its uncertainty has negative impacts in localization and mapping (i.e. SLA…
The work presented in this paper describes the use and evaluation of machine learning techniques like neural networks and support vector regression to learn a model of magnetic field distortions often induced in inertial measurement units using magnetometers by changing currents, postures or configu…
This paper presents the control strategies used to adapt the actively articulated suspension system of the rover SherpaTT to irregular terrain. Experimental validation of the approach with the physical system is conducted and presented. The coordinated control of the legs constituting the suspension…
This paper presents the mechanical development and testing of a docking device for a highly heterogeneous self-reconfigurable multi-module/multi-robot system. The overall system is meant to emulate a robotic lunar exploration mission. The docking device, more precisely the electro-mechanical interfa…
Kinematically complex robots such as legged robots provide a large degree of mobility and flexibility, but demand a sophisticated motion control, which has more tunable parameters than a general planning and decision layer should take into consideration. A lot of parameterizations exist which produc…