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We present CompoSuite, an open-source simulated robotic manipulation benchmark for compositional multi-task reinforcement learning (RL). Each CompoSuite task requires a particular robot arm to manipulate one individual object to achieve a…

Machine Learning · Computer Science 2022-07-12 Jorge A. Mendez , Marcel Hussing , Meghna Gummadi , Eric Eaton

In this paper we present a simulation framework for the evaluation of the navigation and localization metrological performances of a robotic platform. The simulator, based on ROS (Robot Operating System) Gazebo, is targeted to a…

Robotics · Computer Science 2020-06-18 Riccardo Giubilato , Andrea Masili , Sebastiano Chiodini , Marco Pertile , Stefano Debei

Deploying robots at scale demands robustness to the long tail of everyday situations. The countless variations in scene layout, object geometry, and task specifications that characterize real environments are vast and underrepresented in…

We introduce BenchBot, a novel software suite for benchmarking the performance of robotics research across both photorealistic 3D simulations and real robot platforms. BenchBot provides a simple interface to the sensorimotor capabilities of…

Robotics · Computer Science 2020-08-04 Ben Talbot , David Hall , Haoyang Zhang , Suman Raj Bista , Rohan Smith , Feras Dayoub , Niko Sünderhauf

Simulators are a critical component of modern robotics research. Strategies for both perception and decision making can be studied in simulation first before deployed to real world systems, saving on time and costs. Despite significant…

Machine Learning · Computer Science 2020-11-19 Bhairav Mehta , Ankur Handa , Dieter Fox , Fabio Ramos

We tackle the recently introduced benchmark for whole-body humanoid control HumanoidBench using MuJoCo MPC. We find that sparse reward functions of HumanoidBench yield undesirable and unrealistic behaviors when optimized; therefore, we…

Robotics · Computer Science 2024-08-02 Moritz Meser , Aditya Bhatt , Boris Belousov , Jan Peters

We present the first unified, modular, open-source 3DGS-based simulation framework for Real2Sim2Real robot learning. It features a holistic Real2Sim pipeline that synthesizes hyper-realistic geometry and appearance of complex real-world…

This work re-implements the OpenAI Gym multi-goal robotic manipulation environment, originally based on the commercial Mujoco engine, onto the open-source Pybullet engine. By comparing the performances of the Hindsight Experience…

Robotics · Computer Science 2023-03-10 Xintong Yang , Ze Ji , Jing Wu , Yu-Kun Lai

We present MuJoCoUni, a downstream MuJoCo distribution for online robot learning and batched physics evaluation. Alongside the open-loop batched trajectory generation already provided by upstream mujoco.rollout, MuJoCoUni supplies runtime…

Robotics · Computer Science 2026-05-26 Yufei Jia , Junzhe Wu

This paper introduces Unity RL Playground, an open-source reinforcement learning framework built on top of Unity ML-Agents. Unity RL Playground automates the process of training mobile robots to perform various locomotion tasks such as…

Robotics · Computer Science 2025-03-10 Linqi Ye , Rankun Li , Xiaowen Hu , Jiayi Li , Boyang Xing , Yan Peng , Bin Liang

This paper presents an open-source, lightweight, yet comprehensive software framework, named RPC, which integrates physics-based simulators, planning and control libraries, debugging tools, and a user-friendly operator interface. RPC…

Robotics · Computer Science 2024-09-17 Seung Hyeon Bang , Carlos Gonzalez , Gabriel Moore , Dong Ho Kang , Mingyo Seo , Luis Sentis

Most existing robotic manipulation benchmarks focus on simplified tabletop scenarios, typically involving a stationary robotic arm interacting with various objects on a flat surface. To address this limitation, we introduce RoboBenchMart, a…

Developing new functionality for underwater robots and testing them in the real world is time-consuming and resource-intensive. Simulation environments allow for rapid testing before field deployment. However, existing tools lack certain…

Robotics · Computer Science 2025-06-10 Mart Kartašev , David Dörner , Özer Özkahraman , Petter Ögren , Ivan Stenius , John Folkesson

It is well known that it is difficult to have a reliable and robust framework to link multi-agent deep reinforcement learning algorithms with practical multi-robot applications. To fill this gap, we propose and build an open-source…

Robotics · Computer Science 2022-09-29 Junfeng Chen , Fuqin Deng , Yuan Gao , Junjie Hu , Xiyue Guo , Guanqi Liang , Tin Lun Lam

Realistic physics engines play a crucial role for learning to manipulate deformable objects such as garments in simulation. By doing so, researchers can circumvent challenges such as sensing the deformation of the object in the realworld.…

Robotics · Computer Science 2025-12-23 David Blanco-Mulero , Oriol Barbany , Gokhan Alcan , Adrià Colomé , Carme Torras , Ville Kyrki

While significant research progress has been made in robot learning for control, unique challenges arise when simultaneously co-optimizing morphology. Existing work has typically been tailored for particular environments or representations.…

A realistic simulation environment is an essential tool in every roboticist's toolkit, with uses ranging from planning and control to training policies with reinforcement learning. Despite the centrality of simulation in modern robotics,…

Robotics · Computer Science 2022-07-18 Brian Acosta , William Yang , Michael Posa

Advanced reverse engineering tools are required to cope with the complexity of software systems and the specific requirements of numerous different tasks (re-architecturing, migration, evolution). Consequently, reverse engineering tools…

This article introduces a software framework for benchmarking robot task scheduling algorithms in dynamic and uncertain service environments. The system provides standardized interfaces, configurable scenarios with movable objects, human…

Robotics · Computer Science 2026-01-06 Wojciech Dudek , Daniel Giełdowski , Dominik Belter , Kamil Młodzikowski , Tomasz Winiarski

OpenSim is a widely used biomechanics simulator with several anatomically accurate human musculo-skeletal models. While OpenSim provides useful tools to analyse human movement, it is not fast enough to be routinely used for emerging…

Quantitative Methods · Quantitative Biology 2022-07-05 Aleksi Ikkala , Perttu Hämäläinen