1 code implementation • 24 Apr 2023 • Mingjie Li, Tharindu Rathnayake, Ben Beck, Lingheng Meng, Zijue Chen, Akansel Cosgun, Xiaojun Chang, Dana Kulić
Instance-level detection aims to detect which vehicle in the scene gives rise to a close pass near miss.
no code implementations • 14 Jul 2021 • Dylan Klein, Akansel Cosgun
We investigate the effect of using human demonstration data in the replay buffer for Deep Reinforcement Learning.
no code implementations • 6 Mar 2021 • Brendan Tidd, Akansel Cosgun, Jurgen Leitner, Nicolas Hudson
While we show the feasibility of our approach in simulation, the difference in performance between simulated and real world scenarios highlight the difficulty of direct sim-to-real transfer for deep reinforcement learning policies.
no code implementations • 23 Jan 2021 • Brendan Tidd, Nicolas Hudson, Akansel Cosgun, Jurgen Leitner
Dynamic platforms that operate over many unique terrain conditions typically require many behaviours.
no code implementations • 2 Jan 2021 • Sourav Garg, Niko Sünderhauf, Feras Dayoub, Douglas Morrison, Akansel Cosgun, Gustavo Carneiro, Qi Wu, Tat-Jun Chin, Ian Reid, Stephen Gould, Peter Corke, Michael Milford
In robotics and related research fields, the study of understanding is often referred to as semantics, which dictates what does the world "mean" to a robot, and is strongly tied to the question of how to represent that meaning.
no code implementations • 1 Nov 2020 • Brendan Tidd, Nicolas Hudson, Akansel Cosgun, Jurgen Leitner
Legged robots often use separate control policiesthat are highly engineered for traversing difficult terrain suchas stairs, gaps, and steps, where switching between policies isonly possible when the robot is in a region that is commonto adjacent controllers.
no code implementations • 8 Oct 2020 • Brendan Tidd, Nicolas Hudson, Akansel Cosgun
Reliable bipedal walking over complex terrain is a challenging problem, using a curriculum can help learning.
no code implementations • 24 Aug 2020 • Sunny Goondram, Akansel Cosgun, Dana Kulic
This paper demonstrates how simulated images can be useful for object detection tasks in the agricultural sector, where labeled data can be scarce and costly to collect.
2 code implementations • 20 Jul 2020 • Jun Kwan, Chinkye Tan, Akansel Cosgun
Human-to-Robot handovers are useful for many Human-Robot Interaction scenarios.
1 code implementation • 2 Jun 2020 • Patrick Rosenberger, Akansel Cosgun, Rhys Newbury, Jun Kwan, Valerio Ortenzi, Peter Corke, Manfred Grafinger
In experiments with 13 objects, the robot was able to successfully take the object from the human in 81. 9% of the trials.
no code implementations • 2 May 2020 • Shray Bansal, Rhys Newbury, Wesley Chan, Akansel Cosgun, Aimee Allen, Dana Kulić, Tom Drummond, Charles Isbell
We compare two robot modes in a shared table pick-and-place task: (1) Task-oriented: the robot only takes actions to further its own task objective and (2) Supportive: the robot sometimes prefers supportive actions to task-oriented ones when they reduce future goal-conflicts.
no code implementations • 7 Aug 2018 • Shray Bansal, Akansel Cosgun, Alireza Nakhaei, Kikuo Fujimura
Driving is a social activity: drivers often indicate their intent to change lanes via motion cues.
no code implementations • 1 Jun 2018 • Priyam Parashar, Akansel Cosgun, Alireza Nakhaei, Kikuo Fujimura
This paper presents a learning from demonstration approach to programming safe, autonomous behaviors for uncommon driving scenarios.
1 code implementation • 28 Feb 2018 • David Isele, Akansel Cosgun
Deep reinforcement learning has emerged as a powerful tool for a variety of learning tasks, however deep nets typically exhibit forgetting when learning multiple tasks in sequence.
no code implementations • 30 Nov 2017 • David Isele, Akansel Cosgun
We view intersection handling on autonomous vehicles as a reinforcement learning problem, and study its behavior in a transfer learning setting.
no code implementations • 2 May 2017 • Akansel Cosgun, Lichao Ma, Jimmy Chiu, Jiawei Huang, Mahmut Demir, Alexandre Miranda Anon, Thang Lian, Hasan Tafish, Samir Al-Stouhi
Each year, millions of motor vehicle traffic accidents all over the world cause a large number of fatalities, injuries and significant material loss.
no code implementations • 2 May 2017 • David Isele, Akansel Cosgun, Kikuo Fujimura
We analyze how the knowledge to autonomously handle one type of intersection, represented as a Deep Q-Network, translates to other types of intersections (tasks).
no code implementations • 2 May 2017 • David Isele, Reza Rahimi, Akansel Cosgun, Kaushik Subramanian, Kikuo Fujimura
Providing an efficient strategy to navigate safely through unsignaled intersections is a difficult task that requires determining the intent of other drivers.
no code implementations • 14 Apr 2017 • Maxime Bouton, Akansel Cosgun, Mykel J. Kochenderfer
Urban intersections represent a complex environment for autonomous vehicles with many sources of uncertainty.
Robotics