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Aerial Gym Simulator: A Framework for Highly Parallelized Simulation of Aerial Robots
This paper contributes the Aerial Gym Simulator, a highly parallelized, modular framework for simulation and rendering of arbitrary multirotor platforms based on NVIDIA Isaac Gym. Aerial Gym supports the simulation of under-, fully- and over-actuated multirotors offering parallelized geometric controllers, alongside a custom GPU-accelerated rendering framework for ray-casting capable of capturing ...Show More
Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned
Marco Tranzatto;Mihir Dharmadhikari;Lukas Bernreiter;Marco Camurri;Shehryar Khattak;Frank Mascarich;Patrick Pfreundschuh;David Wisth;Samuel Zimmermann;Mihir Kulkarni;Victor Reijgwart;Benoit Casseau;Timon Hornberger;Paolo De Petris;Lionel Ott;Wayne Tubby;Gabriel Waibel;Huan Nguyen;Cesar Cadena;Russell Buchanan;Lorenz Wellhausen;Nikhil Khedekar;Olov Andersson;Lintong Zhang;Takahiro Miki;Tung Dang;Matias Mattamala;Markus Montenegro;Konrad Meyer;Xiangyu Wu;Adrien Briod;Mark Mueller;Maurice Fallon;Roland Siegwart;Marco Hutter;Kostas Alexis
This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with the vision to facilitate the novel technologies necessary to reliably explore diverse underground environments despite the grueling challenges they present for robotic autonomy. Due to their geometric complexity, degrad...Show More
Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned
Marco Tranzatto;Mihir Dharmadhikari;Lukas Bernreiter;Marco Camurri;Shehryar Khattak;Frank Mascarich;Patrick Pfreundschuh;David Wisth;Samuel Zimmermann;Mihir Kulkarni;Victor Reijgwart;Benoit Casseau;Timon Hornberger;Paolo De Petris;Lionel Ott;Wayne Tubby;Gabriel Waibel;Huan Nguyen;Cesar Cadena;Russell Buchanan;Lorenz Wellhausen;Nikhil Khedekar;Olov Andersson;Lintong Zhang;Takahiro Miki;Tung Dang;Matias Mattamala;Markus Montenegro;Konrad Meyer;Xiangyu Wu;Adrien Briod;Mark Mueller;Maurice Fallon;Roland Siegwart;Marco Hutter;Kostas Alexis
Robust High-Speed State Estimation for Off-Road Navigation Using Radar Velocity Factors
Morten Nissov;Jeffrey A. Edlund;Patrick Spieler;Curtis Padgett;Kostas Alexis;Shehryar Khattak
Enabling robot autonomy in complex environments for mission critical application requires robust state estimation. Particularly under conditions where the exteroceptive sensors, which the navigation depends on, can be degraded by environmental challenges thus, leading to mission failure. It is precisely in such challenges where the potential for Frequency Modulated Continuous Wave (FMCW) radar sen...Show More
Probabilistic Degeneracy Detection for Point-to-Plane Error Minimization
Degeneracies arising from uninformative geometry are known to deteriorate LiDAR-based localization and mapping. This work introduces a new probabilistic method to detect and mitigate the effect of degeneracies in point-to-plane error minimization. The noise on the Hessian of the point-to-plane optimization problem is characterized by the noise on points and surface normals used in its construction...Show More
ResiVis: A Holistic Underwater Motion Planning Approach for Robust Active Perception Under Uncertainties
Marios Xanthidis;Martin Skaldebø;Bent Haugaløkken;Linn Evjemo;Kostas Alexis;Eleni Kelasidi
Motion planning for autonomous active perception in cluttered environments remains a challenging problem, requiring real-time solutions that both maximize safety and achieve a desired behavior. In dynamic underwater environments, such as in aquaculture operations, the robots are additionally expected to deal with state and motion uncertainty and errors, dynamic and deformable obstacles, currents, ...Show More
N-MPC for Deep Neural Network-Based Collision Avoidance exploiting Depth Images
2024 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2024 | Conference Paper |
Cited by: Papers (1)
This paper introduces a Nonlinear Model Predictive Control (N-MPC) framework exploiting a Deep Neural Network for processing onboard-captured depth images for collision avoidance in trajectory-tracking tasks with UAVs. The network is trained on simulated depth images to output a collision score for queried 3D points within the sensor field of view. Then, this network is translated into an algebrai...Show More
ROAMER: Robust Offroad Autonomy using Multimodal State Estimation with Radar Velocity Integration
Morten Nissov;Shehryar Khattak;Jeffrey A. Edlund;Curtis Padgett;Kostas Alexis;Patrick Spieler
Reliable offroad autonomy requires low-latency, high-accuracy state estimates of pose as well as velocity, which remain viable throughout environments with sub-optimal operating conditions for the utilized perception modalities. As state estimation remains a single point of failure system in the majority of aspiring autonomous systems, failing to address the environmental degradation the perceptio...Show More
Model Predictive Attitude Control of a Jumping-and-Flying Quadruped for Planetary Exploration
2024 IEEE Aerospace Conference
Year: 2024 | Conference Paper |
Exploration of new planetary environments necessitates the development of novel concepts of locomotion capable of overcoming the potential challenges present on their surface or even in large-scale subsurface voids such as lava tubes. Planets such as Mars present terrain geometries - both on the surface and underground - that may involve steep and tall obstacles or wide but sharp ditches. Walking ...Show More
RMS: Redundancy-Minimizing Point Cloud Sampling for Real-Time Pose Estimation
The typical point cloud sampling methods used in state estimation for mobile robots preserve a high level of point redundancy. This redundancy unnecessarily slows down the estimation pipeline and may cause drift under real-time constraints. Such undue latency becomes a bottleneck for resource-constrained robots (especially UAVs), requiring minimal delay for agile and accurate operation. We propose...Show More
Present and Future of SLAM in Extreme Environments: The DARPA SubT Challenge
Kamak Ebadi;Lukas Bernreiter;Harel Biggie;Gavin Catt;Yun Chang;Arghya Chatterjee;Christopher E. Denniston;Simon-Pierre Deschênes;Kyle Harlow;Shehryar Khattak;Lucas Nogueira;Matteo Palieri;Pavel Petráček;Matěj Petrlík;Andrzej Reinke;Vít Krátký;Shibo Zhao;Ali-akbar Agha-mohammadi;Kostas Alexis;Christoffer Heckman;Kasra Khosoussi;Navinda Kottege;Benjamin Morrell;Marco Hutter;Fred Pauling;François Pomerleau;Martin Saska;Sebastian Scherer;Roland Siegwart;Jason L. Williams;Luca Carlone
This article surveys recent progress and discusses future opportunities for simultaneous localization and mapping (SLAM) in extreme underground environments. SLAM in subterranean environments, from tunnels, caves, and man-made underground structures on Earth, to lava tubes on Mars, is a key enabler for a range of applications, such as planetary exploration, search and rescue, disaster response, an...Show More
Present and Future of SLAM in Extreme Environments: The DARPA SubT Challenge
Kamak Ebadi;Lukas Bernreiter;Harel Biggie;Gavin Catt;Yun Chang;Arghya Chatterjee;Christopher E. Denniston;Simon-Pierre Deschênes;Kyle Harlow;Shehryar Khattak;Lucas Nogueira;Matteo Palieri;Pavel Petráček;Matěj Petrlík;Andrzej Reinke;Vít Krátký;Shibo Zhao;Ali-akbar Agha-mohammadi;Kostas Alexis;Christoffer Heckman;Kasra Khosoussi;Navinda Kottege;Benjamin Morrell;Marco Hutter;Fred Pauling;François Pomerleau;Martin Saska;Sebastian Scherer;Roland Siegwart;Jason L. Williams;Luca Carlone
ResiPlan: Closing the Planning-Acting Loop for Safe Underwater Navigation
2023 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2023 | Conference Paper |
Cited by: Papers (4)
Autonomous operation in underwater environ-ments is, arguably, one of the most complex domains. It requires safe operations under the presence of unpredictable surge, currents, uncertainty, and dynamic obstacles that challenges to the highest degree real-time motion planning; the primary focus of this paper. Although previous work addressed the problem of safe real-time 3D navigation in cluttered ...Show More
Semantics-aware Exploration and Inspection Path Planning
2023 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2023 | Conference Paper |
Cited by: Papers (8)
This paper contributes a novel strategy for semantics-aware autonomous exploration and inspection path planning. Attuned to the fact that environments that need to be explored often involve a sparse set of semantic entities of particular interest, the proposed method offers volumetric exploration combined with two new planning behaviors that together ensure that a complete mesh model is reconstruc...Show More
Manhole Detection and Traversal for Exploration of Ballast Water Tanks using Micro Aerial Vehicles
Mihir Dharmadhikari;Paolo De Petris;Huan Nguyen;Mihir Kulkarni;Nikhil Khedekar;Kostas Alexis
2023 International Conference on Unmanned Aircraft Systems (ICUAS)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
This paper presents a method for the autonomous exploration of multiple compartments of a Ballast Water Tank inside a vessel using Micro Aerial Vehicles. Navigation across the compartments of ballast tanks often requires the robot to pass through narrow cross-section “manholes” (e.g., 0.8×0.6m). Hence, this work presents an algorithm to explicitly detect and localize such manholes using 3D LiDAR d...Show More
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
Marco Tranzatto;Frank Mascarich;Lukas Bernreiter;Carolina Godinho;Marco Camurri;Shehryar Khattak;Tung Dang;Victor Reijgwart;Johannes Löje;David Wisth;Samuel Zimmermann;Huan Nguyen;Marius Fehr;Lukas Solanka;Russell Buchanan;Marko Bjelonic;Nikhil Khedekar;Mathieu Valceschini;Fabian Jenelten;Mihir Dharmadhikari;Timon Hornberger;Paolo De Petris;Lorenz Wellhausen;Mihir Kulkami;Takahiro Miki;Satchel Hirsch;Markus Montenegro;Christos Papachristos;Fabian Tresoldi;Jan Carius;Giorgio Valsecchi;Joonho Lee;Konrad Meyer;Xiangyu Wu;Juan Nieto;Andy Smith;Marco Hutter;Roland Siegwart;Mark Mueller;Maurice Fallon;Kostas Alexis
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems, as underground settings present key challenges that can render robot autonomy hard to achieve. This problem has motivated the DARPA Subterranean Challenge, where teams of robots search for objects of interest in various underground environments. In response, we present the CERBERUS system-of-syste...Show More
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
Marco Tranzatto;Frank Mascarich;Lukas Bernreiter;Carolina Godinho;Marco Camurri;Shehryar Khattak;Tung Dang;Victor Reijgwart;Johannes Löje;David Wisth;Samuel Zimmermann;Huan Nguyen;Marius Fehr;Lukas Solanka;Russell Buchanan;Marko Bjelonic;Nikhil Khedekar;Mathieu Valceschini;Fabian Jenelten;Mihir Dharmadhikari;Timon Hornberger;Paolo De Petris;Lorenz Wellhausen;Mihir Kulkami;Takahiro Miki;Satchel Hirsch;Markus Montenegro;Christos Papachristos;Fabian Tresoldi;Jan Carius;Giorgio Valsecchi;Joonho Lee;Konrad Meyer;Xiangyu Wu;Juan Nieto;Andy Smith;Marco Hutter;Roland Siegwart;Mark Mueller;Maurice Fallon;Kostas Alexis
Marsupial Walking-and-Flying Robotic Deployment for Collaborative Exploration of Unknown Environments
Paolo De Petris;Shehryar Khattak;Mihir Dharmadhikari;Gabriel Waibel;Huan Nguyen;Markus Montenegro;Nikhil Khedekar;Kostas Alexis;Marco Hutter
2022 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
Year: 2022 | Conference Paper |
Cited by: Papers (9)
This work contributes a marsupial robotic system-of-systems involving a legged and an aerial robot capable of collaborative mapping and exploration path planning that exploits the heterogeneous properties of the two systems and the ability to selectively deploy the aerial system from the ground robot. Exploiting the dexterous locomotion capabilities and long endurance of quadruped robots, the mars...Show More
Risk-aware Motion Planning for Collision-tolerant Aerial Robots subject to Localization Uncertainty
Paolo De Petris;Mihir Dharmadhikari;Huan Nguyen;Kostas Alexis
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
This paper contributes a novel strategy towards risk-aware motion planning for collision-tolerant aerial robots subject to localization uncertainty. Attuned to the fact that micro aerial vehicles are often tasked to navigate within GPS-denied, possibly unknown, confined and obstacle-filled environments the proposed method exploits collision-tolerance at the robot design level to mitigate the risks...Show More
MIMOSA: A Multi-Modal SLAM Framework for Resilient Autonomy against Sensor Degradation
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2022 | Conference Paper |
Cited by: Papers (6)
This paper presents a framework for Multi-Modal SLAM (MIMOSA) that utilizes a nonlinear factor graph as the underlying representation to provide loosely-coupled fusion of any number of sensing modalities. Tailored to the goal of enabling resilient robotic autonomy in GPS-denied and perceptually-degraded environments, MIMOSA currently contains modules for pointcloud registration, fusion of multiple...Show More
RMF-Owl: A Collision-Tolerant Flying Robot for Autonomous Subterranean Exploration
Paolo De Petris;Huan Nguyen;Mihir Dharmadhikari;Mihir Kulkarni;Nikhil Khedekar;Frank Mascarich;Kostas Alexis
2022 International Conference on Unmanned Aircraft Systems (ICUAS)
Year: 2022 | Conference Paper |
Cited by: Papers (18)
This work presents the design, hardware realization, autonomous exploration and object detection capabilities of RMF-Owl, a new collision-tolerant aerial robot tailored for resilient autonomous subterranean exploration. The system is custom built for underground exploration with focus on collision tolerance, resilient autonomy with robust localization and mapping, alongside high-performance explor...Show More
Autonomous Teamed Exploration of Subterranean Environments using Legged and Aerial Robots
Mihir Kulkarni;Mihir Dharmadhikari;Marco Tranzatto;Samuel Zimmermann;Victor Reijgwart;Paolo De Petris;Huan Nguyen;Nikhil Khedekar;Christos Papachristos;Lionel Ott;Roland Siegwart;Marco Hutter;Kostas Alexis
2022 International Conference on Robotics and Automation (ICRA)
Year: 2022 | Conference Paper |
Cited by: Papers (62)
This paper presents a novel strategy for autonomous teamed exploration of subterranean environments using legged and aerial robots. Tailored to the fact that subterranean settings, such as cave networks and underground mines, often involve complex, large-scale and multi-branched topologies, while wireless communication within them can be particularly challenging, this work is structured around the...Show More
Autonomous Teamed Exploration of Subterranean Environments using Legged and Aerial Robots
Mihir Kulkarni;Mihir Dharmadhikari;Marco Tranzatto;Samuel Zimmermann;Victor Reijgwart;Paolo De Petris;Huan Nguyen;Nikhil Khedekar;Christos Papachristos;Lionel Ott;Roland Siegwart;Marco Hutter;Kostas Alexis
Year: 2022 | Conference Paper |
Motion Primitives-based Navigation Planning using Deep Collision Prediction
2022 International Conference on Robotics and Automation (ICRA)
Year: 2022 | Conference Paper |
Cited by: Papers (14)
This paper contributes a method to design a novel navigation planner exploiting a learning-based collision prediction network. The neural network is tasked to predict the collision cost of each action sequence in a predefined motion primitives library in the robot's velocity-steering angle space, given only the current depth image and the estimated linear and angular velocities of the robot. Furth...Show More
Resource-aware Online Parameter Adaptation for Computationally -constrained Visual-Inertial Navigation Systems
2021 20th International Conference on Advanced Robotics (ICAR)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
In this paper, a computational resources-aware parameter adaptation method for visual-inertial navigation systems is proposed with the goal of enabling the improved deployment of such algorithms on computationally constrained systems. Such a capacity can prove critical when employed on ultra-lightweight systems or alongside mission critical computationally expensive processes. To achieve this obje...Show More
This paper presents a review of the design and application of model predictive control strategies for Micro Aerial Vehicles and specifically multirotor configurations such as quadrotors. The diverse set of works in the domain is organized based on the control law being optimized over linear or nonlinear dynamics, the integration of state and input constraints, possible fault-tolerant design, if re...Show More
Hypergame-based Adaptive Behavior Path Planning for Combined Exploration and Visual Search
Mihir Dharmadhikari;Harshal Deshpande;Tung Dang;Kostas Alexis
2021 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2021 | Conference Paper |
Cited by: Papers (2)
In this work, we present an adaptive behavior path planning method for autonomous exploration and visual search of unknown environments. As volumetric exploration and visual coverage of unknown environments, with possibly different sensors, are non-identical objectives, a principled combination of the two is proposed. In particular, the method involves three distinct planning policies, namely expl...Show More
Resilient Collision-tolerant Navigation in Confined Environments
Paolo De Petris;Huan Nguyen;Mihir Kulkarni;Frank Mascarich;Kostas Alexis
2021 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2021 | Conference Paper |
Cited by: Papers (16)
This work presents the design and autonomous navigation policy of the Resilient Micro Flyer, a new type of collision-tolerant robot tailored to fly through extremely confined environments and manhole-sized tubes. The robot maintains a low weight (<500g) and implements a combined rigid-compliant design through the integration of elastic flaps around its stiff collision-tolerant frame. These passive...Show More
Online Recommendation-based Convolutional Features for Scale-Aware Visual Tracking
2021 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
In this paper, we develop an online learning-based visual tracking framework that can optimize the target model and estimate the scale variation for object tracking. We propose a recommender-based tracker, which is capable of selecting the representative convolutional neural network (CNN) layers and feature maps autonomously. In addition, the proposed recommender computes the weights of these laye...Show More
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