Background
Reliable detection and state estimation of road users (cars, bikes, pedestrians, …) is critical to navigation in urban driving environments. In this project, our team will extend the autonomy pipeline for detection and explore multi-sensory methods for 3D object detection using sensing modalities such as vision and range sensors.
Project Objectives
The objectives of this project are as follows:
Preferred Skills
ROS, Python, C++, Deep Learning/ML (3D object detection), 3D computer vision, experience with LIDAR
Project Timeline: at least 2 quarters
Background
Understanding the future states (i.e. 3-10 seconds) of road participants plays an important role in decision-making and navigation. In this project, several long term forecasting and intent recognition strategies will be considered and incorporated into our autonomy stack.
Project Objectives
The objectives of this project are as follows:
Preferred Skills
ROS, Python, C++, ML (prediction), probabilistic state estimation and tracking
Project Timeline: at least 2 quarters
Background
Decision making entails defining a sequence of actions given spatiotemporal information about surrounding agents and obstacles provided by a perception stack. In this project, appropriate behaviors and decision-making strategies will be incorporated into our autonomy stack. Early testing and validation will be performed in simulation; deployment will be performed on full-scale vehicles in an urban setting.
Project Objectives
The objectives of this project are as follows:
Preferred Skills
ROS, Python, C++, ML (imitation learning), graphical models (factor graphs).
Project Timeline: at least 2 quarters
Background
Scene understanding and state estimation of various agents depends on an unified representation of the scene. To facilitate this process, depth estimation and coordinate transformations from a sensor centric to an egocentric perspective are of relevance. In this project, several strategies will be considered for monocular depth estimation using image data and other sensing modalities to supervise the depth estimation process.
Project Objectives
The objectives of this project are as follows:
Preferred Skills
Python, C++, Deep Learning/ML (computer vision), structure from motion, multi-view geometry
Project Timeline: 1-2 quarters
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