Related papers: Aerial Gym Simulator: A Framework for Highly Paral…
In this work we present more comprehensive evaluations on our airborne Gimbal mounted inertial measurement unit (IMU) signal simulator which also considers flight dynamic model (FDM). A flexible IMU signal simulator is an enabling tool in…
Over the past decades, progress in deployable autonomous flight systems has slowly stagnated. This is reflected in today's production air-crafts, where pilots only enable simple physics-based systems such as autopilot for takeoff, landing,…
The rise of embodied AI has greatly improved the possibility of general mobile agent systems. At present, many evaluation platforms with rich scenes, high visual fidelity and various application scenarios have been developed. In this paper,…
Simulation engines are widely adopted in robotics. However, they lack either full simulation control, ROS integration, realistic physics, or photorealism. Recently, synthetic data generation and realistic rendering has advanced tasks like…
Musculoskeletal modeling and simulations enable the accurate description and analysis of the movement of biological systems with applications such as rehabilitation assessment, prosthesis, and exoskeleton design. However, the widespread…
Augmented Reality (AR) systems describe the class of systems that use computers to overlay virtual information on the real world. AR environments allow the development of promising tools in several application domains. In medical training…
This paper explores policy-learning approaches in the context of sim-to-real transfer for robotic manipulation using a TIAGo mobile manipulator, focusing on two state-of-art simulators, Isaac Gym and Isaac Sim, both developed by Nvidia.…
Reinforcement Learning (RL) is a promising solution, allowing Unmanned Underwater Vehicles (UUVs) to learn optimal behaviors through trial and error. However, existing simulators lack efficient integration with RL methods, limiting training…
Wheelchairs and robotic arms enhance independent living by assisting individuals with upper-body and mobility limitations in their activities of daily living (ADLs). Although recent advancements in assistive robotics have focused on…
Differentiable simulators provide an avenue for closing the sim-to-real gap by enabling the use of efficient, gradient-based optimization algorithms to find the simulation parameters that best fit the observed sensor readings. Nonetheless,…
The field of 360-degree omnidirectional understanding has been receiving increasing attention for advancing spatial intelligence. However, the lack of large-scale and diverse data remains a major limitation. In this work, we propose…
Bionic underwater robots have demonstrated their superiority in many applications. Yet, training their intelligence for a variety of tasks that mimic the behavior of underwater creatures poses a number of challenges in practice, mainly due…
This paper presents the ARCAD simulator for the rapid development of Unmanned Aerial Systems (UAS), including underactuated and fully-actuated multirotors, fixed-wing aircraft, and Vertical Take-Off and Landing (VTOL) hybrid vehicles. The…
Robotic-assisted medical systems (RAMS) have gained significant attention for their advantages in alleviating surgeons' fatigue and improving patients' outcomes. These systems comprise a range of human-computer interactions, including…
Expressive motion planning for Aerial Manipulators (AMs) is essential for tackling complex manipulation tasks, yet achieving coupled trajectory planning adaptive to various tasks remains challenging, especially for those requiring…
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…
Roadheader is an engineering robot widely used in underground engineering and mining industry. Interactive dynamics simulation of roadheader is a fundamental problem in unmanned excavation and virtual reality training. However, current…
In this work, we introduce OmniDrones, an efficient and flexible platform tailored for reinforcement learning in drone control, built on Nvidia's Omniverse Isaac Sim. It employs a bottom-up design approach that allows users to easily design…
Action-conditioned video prediction models (often referred to as world models) have shown strong potential for robotics applications, but existing approaches are often slow and struggle to capture physically consistent interactions over…
We present a novel framework demonstrating zero-shot sim-to-real transfer of visual control policies learned in a Neural Radiance Field (NeRF) environment for quadrotors to fly through racing gates. Robust transfer from simulation to real…