Chistopher Grebe

Currently working on sensor fusion for autonomy in agriculture and construction at Trimble Autonomous Solutions. Previously a graduate researcher at the University of Toronto Institute for Aerospace Studies and Robotics Institute working in the Space and Terrestrial Autonomous Robotic Systems (STARS) Lab under supervision of Dr. Jonathan Kelly. Prior to joining the STARS Lab, I spent time working on research and development for lidar at Neptec Technologies and for software defined networking at Nokia. This website highlights some of my projects and publications. For any questions, feel free to reach out to christopher.grebe(at)outlook(dot)com.

Below are some of the projects I have worked on…

Lidar-Based UAV Tracking

Performed multi-UAV tracking based on lidar point cloud data through filter-based state estimation, data association and outlier rejection. Lidar sensors provide the ability to effectively and spatially locate UAVs in areas such as airports where unaccounted for UAVs pose a significant risk to the general public. The above image shows collection of the mutli-UAV datset using Neptec's OPAL lidar.

Radar-Camera EKF

Implemented a radar-camera EKF with data association and outlier rejection for the course AER 1513H State Estimation for Aerospace Vehicles. Project utilized a Continental ARS4-A 2D automotive radar and simulated camera data to estimate the position of a radar corner reflector. Ground truth data was obtained using a Vicon motion capture system. Additional results for this project can be seen via video or report.

Lidar for Security Applications

Modeled, simulated and experimentally verified OPAL Lidar viability in various applications. Publicly available information can be found in the paper Aerial and Surface Security Applications Using Lidar. The above image was taken during field testing.

Automotive Lidar R&D

Contributions to R&D of automotive lidar sensor resulted in increased sensor performance. See the international patent application for public information.

Software Defined Networking

Worked on software development project with the Optical Networking Unit involving Nokia's Photonic Service Switch (PSS) and open source Open Network Operating System (ONOS). (photo credit: opennetworking.org)

Perception for Self-Driving

Various perception work on the KITTI Dataset completed for the course AER 1515H Perception for Robotics. Work included stereo vision feature detection, matching and outlier rejection through epipolar geometry-based RANSAC (top image) as well as multi-vehicle tracking using lidar (bottom image).

Sensor-Based Automotive Mirror

Replaced the side mirror of a car with a low cost camera and Lidar sensor for an undergraduate project. A display mounted inside the car provides the driver with a mirror feed overlayed with detected vehicles and a colored warning system based on the speed of the passing vehicle.

Ultrasonic Detection and Reconstruction

Worked on acoustic sensing with the MicroNano Mechatronic Lab. Developed the sensor hardware, software and signal processing pipeline to perform object detection and reconstruction using inexpensive acoustic sensing.

Learning to Detect Slip with Barometric Tactile Sensors and a Temporal Convolutional Neural Network

Abhinav Grover, Philippe Nadeau, Christopher Grebe, Jonathan Kelly
IEEE International Conference on Robotics and Automation (ICRA) 2022

Christopher Grebe

Projects

Lidar-Based UAV Tracking

Radar-Camera EKF

Lidar for Security Applications

Automotive Lidar R&D

Software Defined Networking

Perception for Self-Driving

Sensor-Based Automotive Mirror

Ultrasonic Detection and Reconstruction

Publications

Learning to Detect Slip with Barometric Tactile Sensors and a Temporal Convolutional Neural Network

A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems

Observability-Aware Trajectory Optimization: Theory, Viability & State of the Art

Under Pressure: Learning to Detect Slip with Barometric Tactile Sensors

A Continuous-Time Approach for 3D Radar to Camera Extrinsic Calibration

Monostatic Scanning Lidar Using a Multi-Faceted Polygon Mirror as One of Dual Redirecting Elements

Aerial and Surface Security Applications Using Lidar

A New Real-time Signal Processing Approach for Frequency-varying Machinery