Evaluation of physics engines for robotic simulations with a special focus on the dynamics of walking robots

Roennau, Arne; Sutter, Florian; Heppner, G.; Oberlaender, Jan; Dillmann, Ruediger

doi:10.1109/icar.2013.6766527

Cited by 18 publications

(11 citation statements)

References 8 publications

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“…The reality gap between simulated outcomes and the real world experiment depends on various factors: The simulation software, computational power, which includes memory and CPU cores as well as the ability of using multiple CPU cores [23], and physics engines used within the simulation software [24,25]. Often, a distinction is made between open source and commercial [26], which relates to both software and physics engines.…”

Section: Solution Methodsmentioning

confidence: 99%

Discussing the Reality Gap by Comparing Physics Engines in Kilobot Simulations

Meier

Carroccio

Dornberger

et al. 2021

jrc

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The difference between real experiments and their simulated counterparts, the so-called reality gap, is dependent on various factors and a challenging issue for every simulation-based robot experiment. The reality gap in robot experiments is often caused by software, which is not always able to sufficiently capture particular details and process them properly. In order to minimize this difference, this paper strives to assess different simulation physics engines in V-REP, the simulation framework for the Kilobot swarm robots. The outcome of the simulation software adaption is based on a unified multi robot experiment applied to Kilobots. This paper proposes a simulation attitude, which reflects the outcomes of a real world experiment with Kilobots accurately.

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Section: Solution Methodsmentioning

confidence: 99%

Discussing the Reality Gap by Comparing Physics Engines in Kilobot Simulations

Meier

Carroccio

Dornberger

et al. 2021

jrc

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“…These algorithms and approximations are similar in the most physics engine, but there are significant differences in detail. In previous work, we evaluated three different physics engines with the aim to find the best suited engine for walking robot simulations [14]. Fig.…”

Section: Requirements For Simulation Of Multi-legged Robotsmentioning

confidence: 99%

“…Some of these requirements are directly related to the underlying physics engine used in the simulation. comparison of the underlying friction model [14] There are several advanced real-time capable physics engines that can be used to simulate robotics applications. Deciding which engine to use strongly depends on the requirements of the scenario.…”

Section: Requirements For Simulation Of Multi-legged Robotsmentioning

confidence: 99%

RoaDS — Robot and dynamics simulation for biologically-inspired multi-legged walking robots

Roennau

Heppner

Klemm

et al. 2015

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Increasing computational power and efficient physics engines make robotic simulations popular and applied in more and more domains and scenarios. Well established simulators like GAZEBO have become an important part in robotics research. Nevertheless, non of the popular simulators addresses the needs of multi-legged walking robots. In this work, we develop an efficient and precise simulation system for multi-legged robots: RoaDS. The requirements, architecture and distributed design are presented. A series of experiments with the six-legged walking robot LAURON evaluates and confirms its high accuracy and good performance. RoaDS is a great tool to compare designs of bio-inspired robots, analyze walking patterns and improve robot walking skills.

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“…The robot has to reason over a history of partial observations to efficiently explore where the target object might be. Furthermore, it is notoriously hard to predict the outcome of an action in multicontact physics environments [4], [5], [6], [7]. Modelling error on the physics parameters such as friction, inertia, and objects shapes impede open-loop execution of long action sequences.…”

Section: Introductionmentioning

confidence: 99%

Occlusion-Aware Search for Object Retrieval in Clutter

Bejjani

Agboh

Dogar

et al. 2021

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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We address the manipulation task of retrieving a target object from a cluttered shelf. When the target object is hidden, the robot must search through the clutter for retrieving it. Solving this task requires reasoning over the likely locations of the target object. It also requires physics reasoning over multi-object interactions and future occlusions. In this work, we present a data-driven hybrid planner for generating occlusionaware actions in closed-loop. The hybrid planner explores likely locations of the occluded target object as predicted by a learned distribution from the observation stream. The search is guided by a heuristic trained with reinforcement learning to act on observations with occlusions. We evaluate our approach in different simulation and real-world settings (video available on https://youtu.be/dY7YQ3LUVQg). The results validate that our approach can search and retrieve a target object in near real time in the real world while only being trained in simulation.

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Evaluation of physics engines for robotic simulations with a special focus on the dynamics of walking robots

Cited by 18 publications

References 8 publications

Discussing the Reality Gap by Comparing Physics Engines in Kilobot Simulations

Discussing the Reality Gap by Comparing Physics Engines in Kilobot Simulations

RoaDS — Robot and dynamics simulation for biologically-inspired multi-legged walking robots

Occlusion-Aware Search for Object Retrieval in Clutter

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