Whole-Body Teleoperation and Shared Control of Redundant Robots with Applications to Aerial Manipulation

Coelho, Andre; Sarkisov, Yu. S.; Wu, Xuwei; Mishra, Hrishik; Singh, Harsimran; Dietrich, Alexander; Franchi, Antonio; Kondak, Konstantin; Ott, Christian

doi:10.1007/s10846-021-01365-7

Cited by 21 publications

(12 citation statements)

References 48 publications

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“…Additional sensors may instead simply add more advantageous data, such as egocentric cameras that provide a better detailed view, or exocentric cameras to provide a better sense of where the robot is in its environment ( Saakes et al, 2013 ; Seo et al, 2017a ). Entire other robots may be added to provide more abilities and viewpoints ( Saakes et al, 2013 ; Rakita et al, 2019a ; Coelho et al, 2021 ).…”

Section: Core Problems In Teleoperation Interactionmentioning

confidence: 99%

“…Teleoperation research has long noted that one of the bottlenecks to teleoperation performance is the operator’s abilities, which can be limited by the technology itself, such as camera field of view ( Endsley, 1988 ; Yanco et al, 2004 ; Chen et al, 2007 ; Lin et al, 2007 ; Niemeyer et al, 2016 ). In light of this, a long-term effective strategy for research is to create robots and interfaces that specifically reduce these limiting factors of the robot, such as adding additional camera views ( Saakes et al, 2013 ; Rakita et al, 2019a ), leveraging multiple robots semi-autonomously ( Rakita et al, 2019b ; Coelho et al, 2021 ), or inventing new ways to control robots ( Escolano et al, 2012 ; Choi et al, 2018 ). This research has resulted in numerous new techniques that can benefit numerous teleoperation scenarios.…”

Section: Introductionmentioning

confidence: 99%

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Still Not Solved: A Call for Renewed Focus on User-Centered Teleoperation Interfaces

Rea

Seo

2022

Front. Robot. AI

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Teleoperation is one of the oldest applications of human-robot interaction, yet decades later, robots are still difficult to control in a variety of situations, especially when used by non-expert robot operators. That difficulty has relegated teleoperation to mostly expert-level use cases, though everyday jobs and lives could benefit from teleoperated robots by enabling people to get tasks done remotely. Research has made great progress by improving the capabilities of robots, and exploring a variety of interfaces to improve operator performance, but many non-expert applications of teleoperation are limited by the operator’s ability to understand and control the robot effectively. We discuss the state of the art of user-centered research for teleoperation interfaces along with challenges teleoperation researchers face and discuss how an increased focus on human-centered teleoperation research can help push teleoperation into more everyday situations.

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Section: Core Problems In Teleoperation Interactionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Still Not Solved: A Call for Renewed Focus on User-Centered Teleoperation Interfaces

Rea

Seo

2022

Front. Robot. AI

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“…An initial approach to cope with the aforementioned issues was introduced in Coelho et al (2020) and a complete solution was subsequently presented in Coelho et al (2021). A conceptual view of the presented approach is shown in Figure 14 together with an overview of an experimental scenario.…”

Section: Aerial Manipulation (Hierarchical Bilateral Teleoperation and Haptic Augmentation)mentioning

confidence: 99%

Model-Augmented Haptic Telemanipulation: Concept, Retrospective Overview, and Current Use Cases

et al. 2021

Self Cite

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Certain telerobotic applications, including telerobotics in space, pose particularly demanding challenges to both technology and humans. Traditional bilateral telemanipulation approaches often cannot be used in such applications due to technical and physical limitations such as long and varying delays, packet loss, and limited bandwidth, as well as high reliability, precision, and task duration requirements. In order to close this gap, we research model-augmented haptic telemanipulation (MATM) that uses two kinds of models: a remote model that enables shared autonomous functionality of the teleoperated robot, and a local model that aims to generate assistive augmented haptic feedback for the human operator. Several technological methods that form the backbone of the MATM approach have already been successfully demonstrated in accomplished telerobotic space missions. On this basis, we have applied our approach in more recent research to applications in the fields of orbital robotics, telesurgery, caregiving, and telenavigation. In the course of this work, we have advanced specific aspects of the approach that were of particular importance for each respective application, especially shared autonomy, and haptic augmentation. This overview paper discusses the MATM approach in detail, presents the latest research results of the various technologies encompassed within this approach, provides a retrospective of DLR's telerobotic space missions, demonstrates the broad application potential of MATM based on the aforementioned use cases, and outlines lessons learned and open challenges.

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“…This paper was recommended for publication by Editor Pauline Pounds upon evaluation of the Associate Editor and Reviewers' comments. approach in the literature employs passivity-based control laws, that are notably robust against disturbances [10], [11]. In this scenario, energy tanks have been successfully exploited to increase the robustness of the overall control algorithm [12], [13].…”

Section: Introductionmentioning

confidence: 99%

Power-Based Safety Layer for Aerial Vehicles in Physical Interaction Using Lyapunov Exponents

Eugenio

Lawrance

Tognon

et al. 2022

IEEE Robot. Autom. Lett.

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As the performance of autonomous systems increases, safety concerns arise, especially when operating in nonstructured environments. To deal with these concerns, this work presents a safety layer for mechanical systems that detects and responds to unstable dynamics caused by external disturbances. The safety layer is implemented independently and on top of already present nominal controllers, like pose or wrench tracking, and limits power flow when the system's response would lead to instability. This approach is based on the computation of the Largest Lyapunov Exponent (LLE) of the system's error dynamics, which represent a measure of the dynamics' divergence or convergence rate. By actively computing this metric, divergent and possibly dangerous system behaviors can be promptly detected. The LLE is then used in combination with Control Barrier Functions (CBFs) to impose power limit constraints on a jerk controlled system. The proposed architecture is experimentally validated on an Omnidirectional Micro Aerial Vehicle (OMAV) both in free flight and interaction tasks.

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Whole-Body Teleoperation and Shared Control of Redundant Robots with Applications to Aerial Manipulation

Cited by 21 publications

References 48 publications

Still Not Solved: A Call for Renewed Focus on User-Centered Teleoperation Interfaces

Still Not Solved: A Call for Renewed Focus on User-Centered Teleoperation Interfaces

Model-Augmented Haptic Telemanipulation: Concept, Retrospective Overview, and Current Use Cases

Power-Based Safety Layer for Aerial Vehicles in Physical Interaction Using Lyapunov Exponents

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