Contact Dr. Cang Ye

Phone:(804) 828-0346

Google Voice: (501) 237-1818

Fax: (804) 828-2771   

Email: cye@vcu.edu

Laboratory

Dept. of Computer Science

Virginia Commonwealth University

401 West Main Street, E2264

Richmond, VA 23284-3019

Office

Dept. of Computer Science

Virginia Commonwealth University

401 West Main Street, E2240

Richmond, VA 23284-3019

Robotics Laboratory

Department of Computer Science, College of Engineering

Virginia Commonwealth University

© 2016 Dr. Ye's  LAB. ALL RIGHTS RESERVED.

A Co-Robotic Navigation Aid for the Visually Impaired

The objective of the project is to develop a co-robot cane that may be used by a visually impaired person for wayfinding. The device consist of compute vision module, robotic guide module, and human-device interaction modules. The computer vision module includes 6-DOF SLAM for device pose estimation and mapping, and 3D object recognition. The robotic guide module steer the cane into the desired direction of travel if the robotic guide mode is selected. The human-device interaction module includes a speech interface that allows communication between the cane and the user and a human intent detection interface that senses the user's intent about the desired mode--conventional white cane mode or robotic guide mode--and automatically selects the mode for the user. This project is co-funded by the National Institute of Biomedical Imaging and Bioengineering and the National Eye Institute of the NIH under award R01EB018117.

Overview of the Co-Robot Cane

Click to view video clip of  wayfinding in a home environment

Selected Publications

1. L. Jin, H. Zhang, C. Ye, "Camera Intrinsic Parameters Estimation by Visual Inertial Odometry for a Mobile Phone with Application to Assisted Navigation," IEEE/ASME Transactions on Mechatronics, vol. 25, no. 4, pp. 1803-1811, 2020.
2. 6. H. Zhang and C. Ye, "Plane-Aided Visual-Inertial Odometry for 6-DOF Pose Estimation of a Robotic Navigation Aid," IEEE Access, vol. 8, pp. 90042-90051, 2020.
3. H. Zhang and C. Ye, "An Indoor Wayfinding System based on Geometric Features Aided Graph SLAM for the Visually Impaired," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 25, no. 9, pp. 1592-1604, 2017.
4. C. Ye and X. Qian, "3D Object Recognition of a Robotic Navigation Aid for the Visually Impaired," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 26, no. 2, pp. 441-450, 2018.
5. H. Zhang and C. Ye, “An Indoor navigation aid for the visually impaired,” in IEEE International Conference on Robotics and and Biomimetics (ROBIO), Qingdao, China, 2016.
6. C. Ye, S. Hong, X. Qian, and Wei Wu, "Co-Robotic Cane: A New Robotic Navigation Aid for the Visually Impaired," IEEE System, Man, and Cybernetics Magazine, vol. 2, no. 2, pp. 33-42, 2016.
7. C. Ye, S. Hong, and A. Tamjidi, "6-DOF Pose Estimation of a Robotic Navigation Aid by Tracking Visual and Geometric Features," IEEE Transactions on Automation Science and Engineering, vol. 12, no. 4, pp. 1169-1180, 2015.
8. X. Qian and C. Ye, "NCC-RANSAC: A Fast Plane Extraction Method for 3D Range Data Segmentation," IEEE Transactions on Cybernetics, vol. 44, no. 12, pp. 2771-2783, 2014.
9. H. Zhang and C. Ye, "DUI-VIO: Depth Uncertainty Incorporated Visual Inertial Odometry based on an RGB-D Camera," Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020.
10. H. Zhang, L. Jin, C. Ye, "The VCU-RVI Benchmark: Evaluating Visual Inertial Odometry for Indoor Navigation Applications with an RGB-D Camera," Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020.
11. H. Zhang and C. Ye, "A Visual Positioning System for Indoor Blind Navigation," Proceedings of IEEE International Conference on Robotics and Automation, 2020, pp. 9079-9085.
12. H. Zhang, L. Jin, and C. Ye, "A Depth-Enhanced Visual Inertial Odometry for a Robotic Navigation Aid for Blind People," Visual-Inertial Navigation: Challenges and Applications Workshop at 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems. (received Lord Best Paper Award)
13. S. Hong and C. Ye, "A Pose Graph based Visual SLAM Algorithm for Robot Pose Estimation," in Proceedings of 2014 World Automation Congress, Big Island, HI.
14. C. Ye, S. Hong and X. Qian, "A Co-Robotic Cane for Blind Navigation," in Proceedings of 2014 IEEE International Conference on Systems, Man, and Cybernetics, San Diego, CA.
15. X. Qian and C. Ye, "3D Object Recognition by Geometric Context and Gaussian-Mixture-Model-Based Plane Classification," in Proceedings of 2014 IEEE International Conference on Robotics and Automation, Hong Kong, China.
16. S. Hong and C. Ye, "A Fast Egomotion Estimation Method based on Visual Feature Tracking and Iterative Closest Point," in Proceedings of 2014 IEEE International Conference on Networking, Sensing and Control, Miami, FL. (received Best Student Paper Finalist Award)