Cassie Moves Autonomously
Team: Jonathan Rogers (ME), Bike Zhang (ME), and Shuxiao Chen (IEOR)
Advisors: Koushil Sreenath (ME)
In the field of robotics, legged robot locomotion is one of the hardest problems. We developed a framework for autonomous locomotion. This was accomplished through controllers, path planning, and computer vision.
In 2018, California experienced its deadliest wildfire season in history with over 100 fatalities. Wildfires continue to persist in America and around the globe. Wildfire zones are extremely dangerous and put firefighters’ lives at risk while they perform search and rescue missions.
Robots can serve as a safer and more effective alternative to perform dangerous search and rescue missions. Our research aims to provide a framework for autonomous locomotion combining the agility of a mobile Hovershoes platform and the highly dynamic bipedal robot, “Cassie”, to improve the mobility of legged robotics transportation to wildfire zones.
Our work adds to the field of robotics by proving autonomous, bipedal locomotion on a highly dynamic and moving ground. It also provides a way for transportation that will preserve the energy of the robot so it can perform wildfire search and rescue missions. Furthermore, our work can be applicable to other dangerous environments, such as nuclear leaks and earthquake zones.
Feedback Control for Autonomous Riding of Hovershoes by Cassie Autonomous Robot
Advisor Feature: Koushil Sreenath, Mechanical Engineering
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