Philip Dames

Philip Dames

  • College of Engineering

    Mechanical Engineering

    Associate Professor

Office Location

Engineering 608A

Phone

215-204-7974

Biography

Philip Dames is an Associate Professor of Mechanical Engineering at Temple University, where he directs the Temple Robotics and Artificial Intelligence Lab (TRAIL). Prior to joining Temple, he was a Postdoctoral Researcher in Electrical and Systems Engineering at the University of Pennsylvania. He received his PhD Mechanical Engineering and Applied Mechanics from the University of Pennsylvania in 2015 and his BS and MS degrees in Mechanical Engineering from Northwestern University in 2010. He is the recipient of an NSF CAREER award. His research aims to improve robots’ ability to operate in complex, real-world environments to address societal needs.

Labs: Lab

Research Interests

  • Robotics
  • Active Sensing
  • Multi-Robot Coordination
  • Mapping & Target Tracking.

Courses Taught

Number

Name

Level

ENGR 1102

Introduction to Engineering Problem Solving

Undergraduate

ENGR 2332

Engineering Dynamics

Undergraduate

MEE 3011

Analysis and Computation of Linear Systems in Mechanical Engineering

Undergraduate

MEE 4411

Introduction to Mobile Robotics

Undergraduate

MEE 5110

Special Topics: Robotics at Work - ME Certificate

Graduate

MEE 5411

Introduction to Mobile Robotics

Graduate

MEE 8411

Probabilistic Robotics

Graduate

Selected Publications

  • Xie, Z. & Dames, P. (2024). Semantic2D: A Semantic Dataset for 2D Lidar Semantic Segmentation. Retrieved from http://arxiv.org/

  • Srivastava, A.K. & Dames, P. (2024). Speech-Guided Sequential Planning for Autonomous Navigation using Large
    Language Model Meta AI 3 (Llama3).     Retrieved from http://arxiv.org/

  • Xie, Z. & Dames, P. (2024). SCOPE: Stochastic Cartographic Occupancy Prediction Engine for
    Uncertainty-Aware Dynamic Navigation.     Retrieved from http://arxiv.org/

  • Xin, P., Xie, Z., & Dames, P. (2024). Towards Predicting Collective Performance in Multi-Robot Teams. Retrieved from http://arxiv.org/

  • Chen, T., Shorinwa, O., Bruno, J., Yu, J., Zeng, W., Nagami, K., Dames, P., & Schwager, M. (2024). Splat-Nav: Safe Real-Time Robot Navigation in Gaussian Splatting Maps. Retrieved from http://arxiv.org/

  • Chen, J. & Dames, P. (2023). The Convex Uncertain Voronoi Diagram for Safe Multi-Robot Multi-Target Tracking Under Localization Uncertainty. Journal of Intelligent & Robotic Systems, 109(4). Springer Science and Business Media LLC. doi: 10.1007/s10846-023-01986-0

  • Chen, J., Abugurain, M., Dames, P., & Park, S. (2023). Distributed Multi-Robot Multi-Target Tracking Using Heterogeneous
    Limited-Range Sensors.     Retrieved from http://arxiv.org/

  • Luo, F., Liu, L., Wang, G.G., Kumar, V., Ashton, M.S., Abernethy, J., Afghah, F., Browning, M.H., Coyle, D., Dames, P., O'Halloran, T., Hays, J., Heisl, P., Jiang, C., Khanal, P., Krovi, V.N., Kuebbing, S., Li, N., Liang, J., Liu, N., McNulty, S., Oswalt, C.M., Pederson, N., Terzopoulos, D., Woodall, C.W., Wu, Y., Yang, J., Yang, Y., & Zhao, L. (2023). Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision. 2023 IEEE 5th International Conference on Cognitive Machine Intelligence (CogMI), pp. 1-10. 2023 IEEE 5th International Conference on Cognitive Machine Intelligence (CogMI): IEEE. doi: 10.1109/cogmi58952.2023.00011

  • Xie, Z. & Dames, P. (2023). DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles. IEEE Transactions on Robotics, 39(4), pp. 2700-2719. Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tro.2023.3257549

  • Xie, Z. & Dames, P. (2023). DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using
    Velocity Obstacles.     Retrieved from http://arxiv.org/

  • Xiao, X., Xu, Z., Wang, Z., Song, Y., Warnell, G., Stone, P., Zhang, T., Ravi, S., Wang, G., Karnan, H., Biswas, J., Mohammad, N., Bramblett, L., Peddi, R., Bezzo, N., Xie, Z., & Dames, P. (2022). Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned From the Benchmark Autonomous Robot Navigation Challenge at ICRA 2022 [Competitions]. IEEE Robotics & Automation Magazine, 29(4), pp. 148-156. Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/mra.2022.3213466

  • Xie, Z. & Dames, P. (2022). Stochastic Occupancy Grid Map Prediction in Dynamic Scenes. Retrieved from http://arxiv.org/

  • Chen, J. & Dames, P. (2022). Active Multi-Target Search Using Distributed Thompson Sampling. doi: 10.21203/rs.3.rs-1849567/v1

  • Chen, J. & Dames, P. (2022). The Convex Uncertain Voronoi Diagram for Safe Multi-Robot Multi-Target Tracking Under Localization Uncertainty. doi: 10.21203/rs.3.rs-1530901/v1

  • Chen, J., Xie, Z., & Dames, P. (2022). The semantic PHD filter for multi-class target tracking: From theory to practice. ROBOTICS and AUTONOMOUS SYSTEMS, 149. doi: 10.1016/j.robot.2021.103947

  • Chen, J. & Dames, P. (2022). Multi-class Target Tracking Using the Semantic PHD Filter. ROBOTICS RESEARCH: the 19TH INTERNATIONAL SYMPOSIUM ISRR, 20, pp. 526-541. doi: 10.1007/978-3-030-95459-8_32

  • Xie, Z., Xin, P., Dames, P., & IEEE (2021). Towards Safe Navigation Through Crowded Dynamic Environments. 2021 IEEE/RSJ INTERNATIONAL CONFERENCE on INTELLIGENT ROBOTS and SYSTEMS (IROS), pp. 4934-4940. doi: 10.1109/IROS51168.2021.9636102

  • Chen, J., Dames, P., & IEEE (2021). Distributed Multi-Target Tracking for Heterogeneous Mobile Sensing Networks with Limited Field of Views. 2021 IEEE INTERNATIONAL CONFERENCE on ROBOTICS and AUTOMATION (ICRA 2021), pp. 9058-9064. doi: 10.1109/ICRA48506.2021.9561888

  • Wang, D., Lutz, B., Cobb, P.J., Dames, P., & IEEE (2021). RASCAL: Robotic Arm for Sherds and Ceramics Automated Locomotion. 2021 IEEE INTERNATIONAL CONFERENCE on ROBOTICS and AUTOMATION (ICRA 2021), pp. 6378-6384. doi: 10.1109/ICRA48506.2021.9561057

  • Chen, J. & Dames, P. (2020). Collision-free distributed multi-target tracking using teams of mobile robots with localization uncertainty. IEEE International Conference on Intelligent Robots and Systems, pp. 6968-6974. doi: 10.1109/IROS45743.2020.9341126

  • Chen, J. & Dames, P. (2020). Distributed and Collision-Free Coverage Control of a Team of Mobile Sensors Using the Convex Uncertain Voronoi Diagram. Proceedings of the American Control Conference, 2020-July, pp. 5307-5313. doi: 10.23919/ACC45564.2020.9147359

  • Dames, P.M. (2020). Distributed multi-target search and tracking using the PHD filter. Autonomous Robots, 44(3-4), pp. 673-689. doi: 10.1007/s10514-019-09840-9

  • Cobb, P.J., Earley-Spadoni, T., & Dames, P. (2019). Centimeter-Level Recording for All: Field Experimentation with New, Affordable Geolocation Technology. Advances in Archaeological Practice, 7(4), pp. 353-365. doi: 10.1017/aap.2019.21