112 citations · 552 across the 38 of their papers we have counts for
11 papers · 1 filter
Modeling and Testing Multi-Agent Traffic Rules within Interactive Behavior Planning
Klemens Esterle, Luis Gressenbuch, Alois Knoll
Autonomous vehicles need to abide by the same rules that humans follow. Some of these traffic rules may depend on multiple agents or time. Especially in situations with traffic par…
Formalizing Traffic Rules for Machine Interpretability
Klemens Esterle, Luis Gressenbuch, Alois Knoll
Autonomous vehicles need to be designed to abide by the same rules that humans follow. This is challenging, because traffic rules are fuzzy and not well defined, making them incomp…
Graph Neural Networks and Reinforcement Learning for Behavior Generation in Semantic Environments
Patrick Hart, Alois Knoll
Most reinforcement learning approaches used in behavior generation utilize vectorial information as input. However, this requires the network to have a pre-defined input-size -- in…
Center-of-Mass-based Robust Grasp Planning for Unknown Objects Using Tactile-Visual Sensors
Qian Feng, Zhaopeng Chen, Jun Deng +3
An unstable grasp pose can lead to slip, thus an unstable grasp pose can be predicted by slip detection. A regrasp is required afterwards to correct the grasp pose in order to fini…
Accurate position tracking with a single UWB anchor
Yanjun Cao, Chenhao Yang, Rui Li +2
Accurate localization and tracking are a fundamental requirement for robotic applications. Localization systems like GPS, optical tracking, simultaneous localization and mapping (S…
Task-Independent Spiking Central Pattern Generator: A Learning-Based Approach
Elie Aljalbout, Florian Walter, Florian Röhrbein +1
Legged locomotion is a challenging task in the field of robotics but a rather simple one in nature. This motivates the use of biological methodologies as solutions to this problem.…
Indirect and Direct Training of Spiking Neural Networks for End-to-End Control of a Lane-Keeping Vehicle
Zhenshan Bing, Claus Meschede, Guang Chen +2
Building spiking neural networks (SNNs) based on biological synaptic plasticities holds a promising potential for accomplishing fast and energy-efficient computing, which is benefi…
Lane-Merging Using Policy-based Reinforcement Learning and Post-Optimization
Patrick Hart, Leonard Rychly, Alois Knol
Many current behavior generation methods struggle to handle real-world traffic situations as they do not scale well with complexity. However, behaviors can be learned off-line usin…
Optimal Behavior Planning for Autonomous Driving: A Generic Mixed-Integer Formulation
Klemens Esterle, Tobias Kessler, Alois Knoll
Mixed-Integer Quadratic Programming (MIQP) has been identified as a suitable approach for finding an optimal solution to the behavior planning problem with low runtimes. Logical co…
Counterfactual Policy Evaluation for Decision-Making in Autonomous Driving
Patrick Hart, Alois Knoll
Learning-based approaches, such as reinforcement and imitation learning are gaining popularity in decision-making for autonomous driving. However, learned policies often fail to ge…
Robust Stochastic Bayesian Games for Behavior Space Coverage
Julian Bernhard, Alois Knoll
A key challenge in multi-agent systems is the design of intelligent agents solving real-world tasks in close interaction with other agents (e.g. humans), thereby being confronted w…