Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Karnan, Haresh"'
Autor:
Karnan, Haresh
Publikováno v:
The University of Texas at Austin, May 2024
Recent advances in the field of machine learning have led to new ways for mobile robots to acquire advanced navigational capabilities. However, these learning-based methods raise the possibility that learned navigation behaviors may not align with th
Externí odkaz:
http://arxiv.org/abs/2409.18982
Imitation Learning (IL) strategies are used to generate policies for robot motion planning and navigation by learning from human trajectories. Recently, there has been a lot of excitement in applying IL in social interactions arising in urban environ
Externí odkaz:
http://arxiv.org/abs/2405.16439
Autor:
Karnan, Haresh, Yang, Elvin, Farkash, Daniel, Warnell, Garrett, Biswas, Joydeep, Stone, Peter
Publikováno v:
Conference on Robot Learning (CoRL 2023)
Terrain awareness, i.e., the ability to identify and distinguish different types of terrain, is a critical ability that robots must have to succeed at autonomous off-road navigation. Current approaches that provide robots with this awareness either r
Externí odkaz:
http://arxiv.org/abs/2309.15302
Autor:
Raj, Amir Hossain, Hu, Zichao, Karnan, Haresh, Chandra, Rohan, Payandeh, Amirreza, Mao, Luisa, Stone, Peter, Biswas, Joydeep, Xiao, Xuesu
Empowering robots to navigate in a socially compliant manner is essential for the acceptance of robots moving in human-inhabited environments. Previously, roboticists have developed geometric navigation systems with decades of empirical validation to
Externí odkaz:
http://arxiv.org/abs/2309.13466
Publikováno v:
Under Submission to ICRA 2024
Autonomous mobility tasks such as lastmile delivery require reasoning about operator indicated preferences over terrains on which the robot should navigate to ensure both robot safety and mission success. However, coping with out of distribution data
Externí odkaz:
http://arxiv.org/abs/2309.09912
Autor:
Francis, Anthony, Pérez-D'Arpino, Claudia, Li, Chengshu, Xia, Fei, Alahi, Alexandre, Alami, Rachid, Bera, Aniket, Biswas, Abhijat, Biswas, Joydeep, Chandra, Rohan, Chiang, Hao-Tien Lewis, Everett, Michael, Ha, Sehoon, Hart, Justin, How, Jonathan P., Karnan, Haresh, Lee, Tsang-Wei Edward, Manso, Luis J., Mirksy, Reuth, Pirk, Sören, Singamaneni, Phani Teja, Stone, Peter, Taylor, Ada V., Trautman, Peter, Tsoi, Nathan, Vázquez, Marynel, Xiao, Xuesu, Xu, Peng, Yokoyama, Naoki, Toshev, Alexander, Martín-Martín, Roberto
A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation has advanced tremendously in recent years, the fair evaluation of algori
Externí odkaz:
http://arxiv.org/abs/2306.16740
Autor:
Xiao, Xuesu, Xu, Zifan, Wang, Zizhao, Song, Yunlong, Warnell, Garrett, Stone, Peter, Zhang, Tingnan, Ravi, Shravan, Wang, Gary, Karnan, Haresh, Biswas, Joydeep, Mohammad, Nicholas, Bramblett, Lauren, Peddi, Rahul, Bezzo, Nicola, Xie, Zhanteng, Dames, Philip
The BARN (Benchmark Autonomous Robot Navigation) Challenge took place at the 2022 IEEE International Conference on Robotics and Automation (ICRA 2022) in Philadelphia, PA. The aim of the challenge was to evaluate state-of-the-art autonomous ground na
Externí odkaz:
http://arxiv.org/abs/2208.10473
Autor:
Atreya, Pranav, Karnan, Haresh, Sikand, Kavan Singh, Xiao, Xuesu, Rabiee, Sadegh, Biswas, Joydeep
Accurate control of robots at high speeds requires a control system that can take into account the kinodynamic interactions of the robot with the environment. Prior works on learning inverse kinodynamic (IKD) models of robots have shown success in ca
Externí odkaz:
http://arxiv.org/abs/2206.08487
Autor:
Karnan, Haresh, Sikand, Kavan Singh, Atreya, Pranav, Rabiee, Sadegh, Xiao, Xuesu, Warnell, Garrett, Stone, Peter, Biswas, Joydeep
Publikováno v:
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)
One of the key challenges in high speed off road navigation on ground vehicles is that the kinodynamics of the vehicle terrain interaction can differ dramatically depending on the terrain. Previous approaches to addressing this challenge have conside
Externí odkaz:
http://arxiv.org/abs/2203.15983
Autor:
Karnan, Haresh, Nair, Anirudh, Xiao, Xuesu, Warnell, Garrett, Pirk, Soeren, Toshev, Alexander, Hart, Justin, Biswas, Joydeep, Stone, Peter
Publikováno v:
Robotics and Automation Letters (RA-L) 2022
Social navigation is the capability of an autonomous agent, such as a robot, to navigate in a 'socially compliant' manner in the presence of other intelligent agents such as humans. With the emergence of autonomously navigating mobile robots in human
Externí odkaz:
http://arxiv.org/abs/2203.15041