Our Technologies

Planning is a critical component of any self-driving system. We specialize in developing state-of-the-art technologies for a diverse set of autonomous decision making tasks, including route planning, high-speed motion planning on highways, planning under uncertainty, predicting the intentions of dynamic elements on the road such as other vehicles and pedestrians.

Below are some of our systems in action.

Click to play the high-speed motion planning on the highway video

High-Speed Motion Planning on the Highway

Our planning algorithm generates safe and comfortable motions for self-driving vehicles traveling at high-speeds. Our algorithm can negotiate difficult situations encountered on the highway with high levels of safety, comfortability, and reliability.

Click to play the real-time prediction of intentions video

Real-time Prediction of Intentions

Our prediction algorithms analyze surrounding vehicles, pedestrians, and other dynamic objects in the environment to determine their intentions. Being able to reliably predict future intentions is integral to the performance of a self-driving vehicle.

Click to play the robust planning in uncertain environments video

Robust Planning in Uncertain Environments

Taking into account uncertainty about the intentions of other objects around a self-driving vehicle (e.g. pedestrians, other vehicles, bicyclists) is critical to making safe and comfortable decisions. We have developed novel algorithms that plan efficiently while explicitly reasoning about the uncertainty in the environment surrounding the self-driving vehicle.

Route Planning

Our route planning algorithms generate a long-term plan from a start location to a destination location, taking into account traffic information, road closures, detours, etc. and adjusts the route of the self-driving vehicle accordingly. We employ state-of-the-art search algorithms that allow us to find routes over large road networks in real-time.

Team

Maxim Likhachev

Founder and CEO

Maxim is a Research Associate Professor with the Robotics Institute and National Robotics Engineering Center (NREC), both part of School of Computer Science, Carnegie Mellon University. He is also an adjunct faculty at the Computer and Information Science department at University of Pennsylvania and a member of the GRASP laboratory.

Mike Cannon

Business Development

Mike works on business & partnership development for RobotWits. Previously he worked in sales and business development for Willis Towers Watson, Liazon and Paychex.

Ellis Ratner

Senior Robotics Researcher

Ellis works on prediction, planning and decision making systems at RobotWits. He is also currently a member of the Berkeley AI Research (BAIR) Lab at the University of California, Berkeley, where he is pursuing a PhD in computer science. Previously, Ellis was a member of the Search-Based Planning Lab (SBPL) at Carnegie Mellon University's Robotics Institute.

Lu Lyu

Senior Robotics Researcher

Lu develops prediction algorithms for on-road environments and works on other software engineering tasks in the context of developing software for self-driving vehicles. Prior to joining RobotWits, Lu worked for two start-ups and has hands-on experience developing robotic hardware, perception, and planning systems. Lu received her MS in Robotic Systems Development from Carnegie Mellon University in 2015.

Ramkumar Natarajan

Robotics Researcher

Ram develops optimization algorithms for planning and decision making and designs fail-operational architecture for planning subsystem in self-driving vehicles. He obtained his Master's in Robotics from Worcester Polytechnic Institute (WPI) in 2017 working alongside at a robotics startup in perception and autonomy systems of a retail store robot. Previously, Ram was a member of Reconfigurable and Intelligent Systems Engineering (RISE) group at Indian Institute of Technology (IIT), Madras.

Jonathan Butzke

Lead Robotics Researcher

Jonathan’s primary responsibility is teaching programmers the intricacies of planning for autonomous vehicles. He obtained his Ph.D. in Robotics from Carnegie Mellon University where he worked in the Search-Based Planning Lab. His research activities include aerial and ground vehicle coordination, exploration of unknown environments, and the hardware design of numerous robots. Prior to his Ph.D. studies, Jonathan was a submarine officer.

Alla Safonova

Project Manager

Alla brings expertise in computer graphics, interfaces, visualization and robotics. Prior to joining RobotWits, Alla worked as an Assistant Professor at University of Pennsylvania. Alla holds her Ph.D. from Carnegie Mellon University and Master's degree from Georgia Institute of Technology, both in Computer Science.