Shubham Vyas — accepted AI-conference papers

2026

Reinforcement Learning for Robust Athletic Intelligence: Lessons from the 2nd “AI Olympics with RealAIGym” Competition

Felix Wiebe, Niccolò Turcato, Alberto Dalla Libera, Jean Seong Bjorn Choe, Bumkyu Choi, Tim Faust +15

ICRA 2026poster

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 …

Cited by 0 Source ↗PDF ↗Scholar ↗

2025

Adaptive Model-Based Control of Quadrupeds via Online System Identification using Kalman Filter

Jonas Haack, Franek Stark, Shubham Vyas, Frank Kirchner, Shivesh Kumar

IROS 2025

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

Cited by 1 Source ↗Scholar ↗

2025

Benchmarking Different QP Formulations and Solvers for Dynamic Quadrupedal Walking

Franek Stark, Jakob Middelberg, Dennis Mronga, Shubham Vyas, Frank Kirchner

ICRA 2025

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

Cited by 6 Source ↗code ↗Scholar ↗

2024

Attitude Control of the Hydrobatic Intervention AUV Cuttlefish using Incremental Nonlinear Dynamic Inversion

Tom Slawik, Shubham Vyas, Leif Christensen, Frank Kirchner

IROS 2024poster

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…

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2024

Model Predictive Parkour Control of a Monoped Hopper in Dynamically Changing Environments

Maximilian Albracht, Shivesh Kumar, Shubham Vyas, Frank Kirchner

RA-L 2024

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

Cited by 4 Source ↗code ↗Scholar ↗

2024

Reinforcement Learning for Athletic Intelligence: Lessons from the 1st “AI Olympics with RealAIGym” Competition

Felix Wiebe, Niccolò Turcato, Alberto Dalla Libera, Chi Zhang, Theo Vincent, Shubham Vyas +9

IJCAI 2024poster

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…

Cited by 11 Source ↗PDF ↗Scholar ↗

2023

AcroMonk: A Minimalist Underactuated Brachiating Robot

Mahdi Javadi, Daniel Harnack, Paula Stocco, Shivesh Kumar, Shubham Vyas, Daniel Pizzutilo +1

RA-L 2023

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.

Cited by 14 Source ↗code ↗Scholar ↗

2022

Robot Dance Generation with Music Based Trajectory Optimization

Melya Boukheddimi, Daniel Harnack, Shivesh Kumar, Rohit Kumar, Shubham Vyas, Octavio Arriaga +1

IROS 2022poster

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…

Cited by 6 Source ↗Scholar ↗