Towards Shared Autonomy Applications using Whole-body Control Formulations of Locomanipulation

Merkt, Wolfgang; Ivan, Vladimir; Yang, Yiming; Vijayakumar, Sethu

doi:10.1109/coase.2019.8843153

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…The Ada500 robot is a high-performance omni-directional Autonomous Mobile Robot (AMR) [26]. The maximum linear acceleration is 0.5 m s −2 , and the maximum angular acceleration is 0.92 rad s −2 .…”

Section: A Simulationsmentioning

confidence: 99%

A Passive Navigation Planning Algorithm for Collision-free Control of Mobile Robots

Tiseo

Ivan

Merkt

et al. 2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

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Path planning and collision avoidance are challenging in complex and highly variable environments due to the limited horizon of events. In literature, there are multiple model-and learning-based approaches that require significant computational resources to be effectively deployed and they may have limited generality. We propose a planning algorithm based on a globally stable passive controller that can plan smooth trajectories using limited computational resources in challenging environmental conditions. The architecture combines the recently proposed fractal impedance controller with elastic bands and regions of finite time invariance. As the method is based on an impedance controller, it can also be used directly as a force/torque controller. We validated our method in simulation to analyse the ability of interactive navigation in challenging concave domains via the issuing of via-points, and its robustness to low bandwidth feedback. A swarm simulation using 11 agents validated the scalability of the proposed method. We have performed hardware experiments on a holonomic wheeled platform validating smoothness and robustness of interaction with dynamic agents (i.e., humans and robots). The computational complexity of the proposed local planner enables deployment with low-power micro-controllers lowering the energy consumption compared to other methods that rely upon numeric optimisation.

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Section: A Simulationsmentioning

confidence: 99%

A Passive Navigation Planning Algorithm for Collision-free Control of Mobile Robots

Tiseo

Ivan

Merkt

et al. 2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

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“…But optimal control is too slow for real time control when considering inequality constraints. A more general framework employing nonlinear programming (NLP) is proposed to cope with planning and control for loco-manipulation of low dimension mobile robots [12] or offline motion planning [13].…”

Section: A Related Workmentioning

confidence: 99%

Variable Autonomy of Whole-body Control for Inspection and Intervention in Industrial Environments using Legged Robots

Xin

Tiseo

Wolfslag

et al. 2020

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)

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The deployment of robots in industrial and civil scenarios is a viable solution to protect operators from danger and hazards. Shared autonomy is paramount to enable remote control of complex systems such as legged robots, allowing the operator to focus on the essential tasks instead of overly detailed execution. To realize this, we propose a comprehensive control framework for inspection and intervention using a legged robot and validate the integration of multiple locomanipulation algorithms optimised for improving the remote operation. The proposed control offers 3 operation modes: fully automated, semi-autonomous, and the haptic interface receiving onsite physical interaction for assisting teleoperation. Our contribution is the design of a QP-based semi-analytical wholebody control, which is the key to the various task completion subject to internal and external constraints. We demonstrate the versatility of the whole-body control in terms of decoupling tasks, singularity tolerance and constraint satisfaction. We deploy our solution in field trials and evaluate in an emergency setting by an E-stop while the robot is clearing road barriers and traversing difficult terrains.

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Section: A Related Workmentioning

confidence: 99%

Variable Autonomy of Whole-body Control for Inspection and Intervention in Industrial Environments using Legged Robots

Xin¹,

Tiseo²,

Wolfslag³

et al. 2020

Preprint

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The deployment of robots in industrial and civil scenarios is a viable solution to protect operators from danger and hazards. Shared autonomy is paramount to enable remote control of complex systems such as legged robots, allowing the operator to focus on the essential tasks instead of overly detailed execution. To realize this, we proposed a comprehensive control framework for inspection and intervention using a legged robot and validated the integration of multiple locomanipulation algorithms optimised for improving the remote operation. The proposed control offers 3 operation modes: fully automated, semi-autonomous, and the haptic interface receiving onsite physical interaction for assisting teleoperation. Our contribution is the design of a QP-based semi-analytical wholebody control, which is the key to the various task completion subject to internal and external constraints. We demonstrated the versatility of the whole-body control in terms of decoupling tasks, singularity toleration and constraint satisfaction. We deployed our solution in field trials and evaluated in an emergency setting by an E-stop while the robot was clearing road barrier and traversing difficult terrains.

show abstract

Towards Shared Autonomy Applications using Whole-body Control Formulations of Locomanipulation

Cited by 8 publications

References 28 publications

A Passive Navigation Planning Algorithm for Collision-free Control of Mobile Robots

A Passive Navigation Planning Algorithm for Collision-free Control of Mobile Robots

Variable Autonomy of Whole-body Control for Inspection and Intervention in Industrial Environments using Legged Robots

Variable Autonomy of Whole-body Control for Inspection and Intervention in Industrial Environments using Legged Robots

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