Hybrid State Estimation and Mode Identification of an Amphibious Robot

C-Ray is an amphibious robot that is capable of swimming in water and crawling on land using its undulating fins, enabling operations in a wide range of environments. The robot can be modeled as a hybrid dynamical system whose dynamics and propulsion change when the robot transitions between water and land. Most importantly, the direction of wave travel in the robot's fins is reversed between its swimming and crawling locomotion styles. To operate autonomously, C-Ray requires both accurate identification of when transitions between water and land occur and robust state estimation in littoral environments where the transition dynamics are highly discontinuous and transient. This paper presents a hybrid observer for estimating continuous states and identifying state-driven mode switches for C-Ray, enabling autonomous water/land-transitions. The proposed observer is a combination of the multiplicative extended Kalman filter (MEKF) and the salted Kalman filter, a newly proposed Kalman filter for mapping state uncertainty during hybrid transitions. We also propose an altitude and sea floor geometry observer and incorporate this directly into the MEKF. The performance is evaluated in simulations.