Tether monitoring for entanglement detection, disentanglement and localisation of autonomous robots

Rajan, Vishnu; Nagendran, Arjun; Dehghani-Sanij, Abbas A.; Richardson, Robert C.

doi:10.1017/s0263574714001623

Cited by 7 publications

(6 citation statements)

References 22 publications

(34 reference statements)

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Section: Overview Of a Multi-robot System Formentioning

confidence: 99%

“…Vehicles that manage cables by adjusting the cable length and tension using cable reels have been developed [18] [19]. In particular, [19] reports an example of cable untying while avoiding the obstacles in a multi-obstacle environment. However, because of the thinness of the target cable, the bending and twisting of the cable were not considered, as they are in the system we propose.…”

Section: Overview Of a Multi-robot System Formentioning

confidence: 99%

See 1 more Smart Citation

Cooperative Towing by Multi-Robot System That Maintains Welding Cable in Optimized Shape

Suzuki

Okada

Yokota

et al. 2022

IEEE Robot. Autom. Lett.

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As considerable amounts of welding are required during ship construction, robotic automation is being promoted. However, current welding robots do not automate work in high or narrow places. One reason is that welding cannot be performed with sufficient accuracy because a welding robot with a torch cannot tow a heavy cable and thus may go off path.This paper proposes a multi-robot system for automating the execution of long welds in high and narrow places to address this problem. In the proposed method, towing vehicles are placed along the supply cable to reduce the load on the lead welding vehicle. In confined-space welding, the cable must not be excessively loaded, and obstacles such as walls must be avoided. Under the proposed method, autonomous movement of the towing vehicles is achieved by solving an optimization problem that considers these aims and minimizes the amount of change from the estimated current cable shape. The method was evaluated through simulation and real-world tests, in which it was applied successfully to tow the cable with a welding torch in a working area of 2.6 × 10 m 2 (simulation) and of 3.4 × 5.5 m 2 (real-world environment) without disturbing the lead vehicle's movement.

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Section: Overview Of a Multi-robot System Formentioning

confidence: 99%

Section: Overview Of a Multi-robot System Formentioning

confidence: 99%

Cooperative Towing by Multi-Robot System That Maintains Welding Cable in Optimized Shape

Suzuki

Okada

Yokota

et al. 2022

IEEE Robot. Autom. Lett.

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“…3 has been adopted. The localisation problem has been solved with a singlewire localisation approach inspired from tethered simultaneous localisation and mapping (TSLAM) [15], relying on the determination of 2 angles (horizontal and vertical rotations) and tether length, as shown in Fig. 4 Figure 4.…”

Section: A Technical Detailsmentioning

confidence: 99%

Tether-Based Localisation System for Underwater Robots

Martin

Tang

2022

2022 27th International Conference on Automation and Computing (ICAC)

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Tank-inspection robotic crawlers often rely on localisation techniques such as dead reckoning to survey walls and surfaces. However, the robot position can drift over time when using these techniques, which therefore require precise calibration. This paper presents a novel tether-based system providing a real-time localisation reference tool to help calibrate and understand prevalent localisation technologies, inside uncluttered tanks. The assessed localisation technologies can subsequently be used in cluttered and complex operational tanks. The developed system relies on a mechanical connection between the tank edge and the robotic crawler and is composed of two distinct units. The first unit is the tether orienting platform clamped onto the tank edge and guiding a tether coming out of a draw-wire position sensor. The second unit is the crawler platform mounted on top of the robotic crawler and holding the tip of the tether, while allowing the robot to move freely. The performance of the system is assessed by determining the accuracy on the 3D position of the robot and the accuracy on its 2D heading, over a 1m x 1m area. The positional accuracy with 90% confidence interval is ±39mm and the heading accuracy with 95% confidence interval is ±4.8°.

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“…Tether measurements have been used in line-of-sight localization for robots by Rajan et al (2014) and Kumar and Richardson (2008). However, these experiments employed brute-force localization and did not use probabilistic machinery.…”

Section: Related Workmentioning

confidence: 99%

TSLAM: Tethered simultaneous localization and mapping for mobile robots

McGarey

MacTavish

Pomerleau

et al. 2017

The International Journal of Robotics Research

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Tethered mobile robots are useful for exploration in steep, rugged, and dangerous terrain. A tether can provide a robot with robust communications, power, and mechanical support, but also constrains motion. In cluttered environments, the tether will wrap around a number of intermediate ‘anchor points’, complicating navigation. We show that by measuring the length of tether deployed and the bearing to the most recent anchor point, we can formulate a tethered simultaneous localization and mapping (TSLAM) problem that allows us to estimate the pose of the robot and the positions of the anchor points, using only low-cost, nonvisual sensors. This information is used by the robot to safely return along an outgoing trajectory while avoiding tether entanglement. We are motivated by TSLAM as a building block to aid conventional, camera, and laser-based approaches to simultaneous localization and mapping (SLAM), which tend to fail in dark and or dusty environments. Unlike conventional range-bearing SLAM, the TSLAM problem must account for the fact that the tether-length measurements are a function of the robot’s pose and all the intermediate anchor-point positions. While this fact has implications on the sparsity that can be exploited in our method, we show that a solution to the TSLAM problem can still be found and formulate two approaches: (i) an online particle filter based on FastSLAM and (ii) an efficient, offline batch solution. We demonstrate that either method outperforms odometry alone, both in simulation and in experiments using our TReX (Tethered Robotic eXplorer) mobile robot operating in flat-indoor and steep-outdoor environments. For the indoor experiment, we compare each method using the same dataset with ground truth, showing that batch TSLAM outperforms particle-filter TSLAM in localization and mapping accuracy, owing to superior anchor-point detection, data association, and outlier rejection.

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Tether monitoring for entanglement detection, disentanglement and localisation of autonomous robots

Cited by 7 publications

References 22 publications

Cooperative Towing by Multi-Robot System That Maintains Welding Cable in Optimized Shape

Cooperative Towing by Multi-Robot System That Maintains Welding Cable in Optimized Shape

Tether-Based Localisation System for Underwater Robots

TSLAM: Tethered simultaneous localization and mapping for mobile robots

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