Radial polar histogram: obstacle avoidance and path planning for robotic cognition and motion control

Wang, Po-Jen; Keyawa, Nicholas R.; Euler, Craig

doi:10.1117/12.909069

Cited by 3 publications

(1 citation statement)

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“…The terrain obstacle detection features are expanded to improve processing with computer cluster hardware for higher resolution RGB images and multiple LRFs. Multiple sensors data is collected instead of a single sensor to improve data resolution and scope for feature detection [8,13,17,[21][22][23].…”

Section: Vision Enhancementmentioning

confidence: 99%

Human-Machine Interface for a Smart Wheelchair

Hartman

Nandikolla

2019

Journal of Robotics

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The paper describes the integration of hardware and software with sensor technology and computer processing to develop the next generation intelligent wheelchair. The focus is a computer cluster design to test high performance computing for smart wheelchair operation and human interaction. The LabVIEW cluster is developed for real-time autonomous path planning and sensor data processing. Four small form factor computers are connected over a Gigabit Ethernet local area network to form the computer cluster. Autonomous programs are distributed across the cluster for increased task parallelism to improve processing time performance. The distributed programs operating frequency for path planning and motion control is 50Hz and 12.3Hz for 0.3 megapixel robot vision system. To monitor the operation and control of the distributed LabVIEW code, network automation is integrated into the cluster software along with a performance monitor. A link between the computer motion control program and the wheelchair joystick control of the drive train is developed for the computer control interface. A perception sensor array and control circuitry is integrated with the computer system to detect and respond to the wheelchair environment. Multiple cameras are used for image processing and scanning laser rangefinder sensors for obstacle avoidance in the cluster program. A centralized power system is integrated to power the smart wheelchair along with the cluster and sensor feedback system. The on board computer system is evaluated for cluster processing performance for the smart wheelchair, incorporating camera machine vision and LiDAR perception for terrain obstacle detection, operating in urban scenarios.

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