Towards Autonomous Multi-Modal Mobility Morphobot (M4) Robot:
Traversability Estimation and 3D Path Planning
by
Rohit Hiraman Rajput
Master of Science in Robotics
Northeastern University, August 2023
Dr. Alireza Ramezani, Dr. Hanumant Singh, Adviser
This thesis enhances the autonomy of the M4 (Multi-Modal Mobility Morphobot) robot,
designed for Mars and rescue missions. The research enables the robot to autonomously select its
locomotion mode and path in complex terrains. Focusing on walking and flying modes, a Gazebo
simulation and custom perception-navigations pipelines are developed. Leveraging deep learning,
the robot determines optimal mode transitions based on a 2.5D map. Additionally, an energy-
efficient path planner based on 2.5D mapping is implemented and validated in simulations. The
contributions demonstrate scalability for future mode integrations. The M4 robot showcases intel-
ligent mode switching, efficient navigation, and reduced energy consumption, bringing us closer
to fully autonomous multi-modal robots for exploration and rescue missions. This work paves the
way for future advancements in autonomous robotics, with the ultimate vision of deploying the M4
robot for exploration and rescue tasks, making a significant impact in the quest for intelligent and
versatile robotic systems.
Multi-modal Mobility Morphobot (M4), a transforming robot
capable of multimodal locomotion, including ground and aerial locomotion
modes.
The Pipeline for Autonomous Navigation of M4 using a single real sense deapth camera
M4 different modes of operation
Elevation mapping live in the Gazebo simulator with mapping with mars environment
The 3Dpath planner is build on top of 2.5D elevation data and edge case analysis is as below :
1st edge case : An inaccessible area via wheeled motion . the path planner computes the cost but determines optimal path
2nd edge case : The barriers show that with flight the end point will be achieved quicker , we use Energy efficiency to optimize the path
3rd edge case : One of the important for crater exploration on mars , going down and detecting the slop and flying over the edge and landing on the flat surface. It wheels towards the edge and flies to optimize energy efficiency
Result summery on energy used and time required with the tests