Autonomous Spot: Long-Range Autonomous Exploration of Extreme Environments with Legged Locomotion

Bouman, Amanda; Ginting, Muhammad Fadhil; Alatur, Nikhilesh; Palieri, Matteo; Fan, David D.; Touma, Thomas; Pailevanian, Torkom; Kim, Sung Kyun; Otsu, Kyohei; Burdick, Joel W.; Agha–mohammadi, Ali–akbar

doi:10.48550/arxiv.2010.09259

Cited by 7 publications

(10 citation statements)

References 6 publications

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“…A single erroneous data association could be catastrophic, as it would render all subsequent measurements useless. Team CoStar introduced heterogeneous redundant odometry (HeRO) to derive estimates from multiple odometry algorithms running in parallel (Santamaria-Navarro et al, 2020;Bouman et al, 2020). Resilience is achieved by ensuring redundancy and initiating recovery.…”

Section: Simultaneously Localization and Mappingmentioning

confidence: 99%

A Heterogeneous Unmanned Ground Vehicle and Blimp Robot Team for Search and Rescue using Data-driven Autonomy and Communication-aware Navigation

Lu¹,

Huang²,

Huang³

et al. 2022

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This paper describes the architecture and implementation of a heterogeneous team comprising unmanned ground vehicles and blimp robots capable of navigating unknown subter- ranean environments for search and rescue missions. The ground vehicles are equipped with a range of sensors for accurate perception, localization, and mapping. The blimps feature a long flight duration and collision tolerance when traversing uneven terrain. The design of the system was meant to satisfy the requirements of the Defense Advanced Research Projects Agency (DARPA) Subterranean Challenge in terms of perception capability and autonomy. To facilitate navigation through smoke-filled spaces, we employed novel millimeter wave radar to enable cross-modal representations for integration via deep reinforcement learning. The autonomy of the proposed scheme was augmented using simulations to train deep neural networks, thereby allowing the system to perform sequential decision-making for collision avoidance and navigation toward a specific goal. The navigation system was evaluated in the DARPA SubT Urban Circuit, and quantitative localization results and recovery strategy from failures was discussed. The proposed communication system comprises mesh WiFi with XBee (ZigBee network with XBee radios) and ultra-wideband (UWB) communication modules as well as spherical nodes that can be shot out like a cannonball and miniature cars deployed as mobile nodes. The propagation and radio signal strength index of various modules were evaluated using data collected during field tests in order to overcome the uncertainties of subterranean environments, including non-line-of-sight propagation, multipath propagation, and fading reception. We also discuss the lessons learned during this project and reflect on future plans.

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Section: Simultaneously Localization and Mappingmentioning

confidence: 99%

A Heterogeneous Unmanned Ground Vehicle and Blimp Robot Team for Search and Rescue using Data-driven Autonomy and Communication-aware Navigation

Lu¹,

Huang²,

Huang³

et al. 2022

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“…Team CoSTAR focuses on their NeBula (Networked Belief-aware Perceptual Autonomy) system, which takes into account the uncertainty of all possible parts and is designed to perform long tasks outside of the range of communications. In [Bouman et al, 2020] they focus on new Boston Dynamics platforms, which with the help of two Husky platforms, won the entire Urban circuit. Legged platforms were deployed earlier in the Tunnel circuit by Pluto [Miller et al, 2020] and Cerberus [Bjelonic et al, 2020] where the legged platforms did not perform well due to slippery surfaces even when equipped with wheels to serve as walking/rolling platform.…”

Section: Related Workmentioning

confidence: 99%

System for multi-robotic exploration of underground environments CTU-CRAS-NORLAB in the DARPA Subterranean Challenge

Rouček¹,

Pecka²,

Čížek³

et al. 2021

Preprint

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We present a field report of CTU-CRAS-NORLAB team from the Subterranean Challenge (SubT) organised by the Defense Advanced Research Projects Agency (DARPA). The contest seeks to advance technologies that would improve the safety and efficiency of searchand-rescue operations in GPS-denied environments. During the contest rounds, teams of mobile robots have to find specific objects while operating in environments with limited radio communication, e.g. mining tunnels, underground stations or natural caverns. We present a heterogeneous exploration robotic system of the CTU-CRAS-NORLAB team, which achieved the third rank at the SubT Tunnel and Urban Circuit rounds and surpassed the performance of all other non-DARPA-funded teams. The field report describes the team's hardware, sensors, algorithms and strategies, and discusses the lessons learned by participating at the DARPA SubT contest.

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“…Consequently, quadrupedal robots are expected to achieve various real-world missions. These vehicles have proven to be extremely robust and can cope with complex environments and terrains, which opened the potential for application in real world missions [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Circus ANYmal: A Quadruped Learning Dexterous Manipulation with Its Limbs

Shi

Homberger

Lee

et al. 2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

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Quadrupedal robots are skillful at locomotion tasks while lacking manipulation skills, not to mention dexterous manipulation abilities. Inspired by the animal behavior and the duality between multi-legged locomotion and multi-fingered manipulation, we showcase a circus ball challenge on a quadrupedal robot, ANYmal. We employ a model-free reinforcement learning approach to train a deep policy that enables the robot to balance and manipulate a light-weight ball robustly using its limbs without any contact measurement sensor. The policy is trained in the simulation, in which we randomize many physical properties with additive noise and inject random disturbance force during manipulation, and achieves zero-shot deployment on the real robot without any adjustment. In the hardware experiments, dynamic performance is achieved with a maximum rotation speed of 15 • /s, and robust recovery is showcased under external poking. To our best knowledge, it is the first work that demonstrates the dexterous dynamic manipulation on a real quadrupedal robot.

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Autonomous Spot: Long-Range Autonomous Exploration of Extreme Environments with Legged Locomotion

Cited by 7 publications

References 6 publications

A Heterogeneous Unmanned Ground Vehicle and Blimp Robot Team for Search and Rescue using Data-driven Autonomy and Communication-aware Navigation

A Heterogeneous Unmanned Ground Vehicle and Blimp Robot Team for Search and Rescue using Data-driven Autonomy and Communication-aware Navigation

System for multi-robotic exploration of underground environments CTU-CRAS-NORLAB in the DARPA Subterranean Challenge

Circus ANYmal: A Quadruped Learning Dexterous Manipulation with Its Limbs

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