Risk Averse Bayesian Reward Learning for Autonomous Navigation from Human Demonstration

Ellis, Christian; Wigness, Maggie; Rogers, John G.; Lennon, Craig; Fiondella, Lance

doi:10.1109/iros51168.2021.9635835

Cited by 2 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…All of the methods mentioned fall into a sub-field known as imitation learning [50]. Lastly, recent developments in imitation learning attempt to incorporate safety as part of the learning process using uncertainty quantification, creating a new sub field known as safe imitation learning [51], [52].…”

Section: B Learning From Human Feedbackmentioning

confidence: 99%

A Mapping of Assurance Techniques for Learning Enabled Autonomous Systems to the Systems Engineering Lifecycle

Ellis

Wigness

Fiondella

2022

2022 IEEE International Conference on Assured Autonomy (ICAA)

Self Cite

View full text Add to dashboard Cite

Learning enabled autonomous systems provide increased capabilities compared to traditional systems. However, the complexity of and probabilistic nature in the underlying methods enabling such capabilities present challenges for current systems engineering processes for assurance, and test, evaluation, verification, and validation (TEVV). This paper provides a preliminary attempt to map recently developed technical approaches in the assurance and TEVV of learning enabled autonomous systems (LEAS) literature to a traditional systems engineering v-model. This mapping categorizes such techniques into three main approaches: development, acquisition, and sustainment. We review the latest techniques to develop safe, reliable, and resilient learning enabled autonomous systems, without recommending radical and impractical changes to existing systems engineering processes. By performing this mapping, we seek to assist acquisition professionals by (i) informing comprehensive test and evaluation planning, and (ii) objectively communicating risk to leaders.

show abstract

Section: B Learning From Human Feedbackmentioning

confidence: 99%

A Mapping of Assurance Techniques for Learning Enabled Autonomous Systems to the Systems Engineering Lifecycle

Ellis

Wigness

Fiondella

2022

2022 IEEE International Conference on Assured Autonomy (ICAA)

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, the cost map has been used to coordinate multiple robots [13]. Ellis et al proposed risk averse bayesian reward learning for autonomous navigation from human demonstration [21].…”

Section: Related Workmentioning

confidence: 99%

Layered-Cost-Map-Based Traffic Management for Multiple AMRs via a DDS

Jeong

Inhwan³

et al. 2022

Applied Sciences

View full text Add to dashboard Cite

A traffic management system can be used to control multiple automated mobile robots (AMRs) effectively. This paper proposes traffic management for multiple AMRs based on a layered cost map in ROS 2 for multiple purposes. Using the layered cost map, the new concepts of a prohibition filter, lane filter, fleet layer, and region filter are proposed and implemented. The prohibition filter can help a user set an area that would prohibit an AMR from trespassing. The lane filter can help set one-way directions based on an angle image. The fleet layer can help AMRs share their locations via the traffic management server. The region filter requests for or receives an exclusive area, which can be occupied by only one AMR from the traffic management server. Multiple AMRs communicate via a data distribution service (DDS), which is shared by topics in the same DDS domain. The traffic management server in the domain sends or receives topics to each of the AMRs. The experiments of AMRs under the proposed traffic management show the effectiveness of our approach.

show abstract

Risk Averse Bayesian Reward Learning for Autonomous Navigation from Human Demonstration

Cited by 2 publications

References 15 publications

A Mapping of Assurance Techniques for Learning Enabled Autonomous Systems to the Systems Engineering Lifecycle

A Mapping of Assurance Techniques for Learning Enabled Autonomous Systems to the Systems Engineering Lifecycle

Layered-Cost-Map-Based Traffic Management for Multiple AMRs via a DDS

Contact Info

Product

Resources

About