Multimodal biomimetic underwater robots (BURs) can conduct underwater tasks suitable for the environment. Combining the characteristics of aquatic organisms enables the swimming and leggedlocomotion required for underwater exploration. Locomotion control mechanism relies on rule-based behavior selection and the designer's discretion. This limits the robot's ability to acquire new behavioral capabilities to the predetermined range of behaviors. To address these challenges, we propose a mechanism and control system that enables the expression of multimodal locomotion capabilities from the same multi-jointed structure. A mechanism equipped with four leg-fins each having four axes is used. This controller achieves nonlinear behavior based on sensor modalities, rather than relying on predefined conditional rule-based on locomotion functions. This system was validated through both physical and simulation testing based on multiple sensor data and behavioral patterns. Utilizing a potential function in multimodal locomotion control was verified to enable transitions between two or three behaviors. Implementing the control method as a multimodal controller is expected to enhance its application in underwater exploration. Our project page is at https://tasada038.github.io/multi-jointed-bur/.
Figures & tables
Figure 1: Prototype of the manta ray robot. (a) overview of the manta ray robot, (b) CPG topological network, (c) mechanical of the leg-fins, (d) DH-parameter of the robot, (e) BVBS mechanical diagram.
Items
Characteristics
Size (L × W × H)
0.38 m × 0.85 m × 0.14 m
Total Mass
8.4 kg
Fin arrangement
fins(yaw, roll, pitch, and roll) × 4
Control mode
Wired control
Controller
Jetson Nano B01, Teensy 4.1
Power Supply
5000 mAh, 7.4V, LiPo battery × 2
Table 1: Technical specifications of the manta ray robot.
Link
θi (deg)
di (mm)
ai (mm)
αi (rad)
0
θinit
0
a0
0
1
θ1+θoffset
0
0
- 2π
2
θ2+2π
0
0
2π
3
θ3
d3
0
- 2π
4
θ4
0
0
2π
E
2π
dE
0
0
Table 2: D-H Parameters of the manta ray robot in NED frame.
Figure 2: Coordinate system of the manta ray robot in the NED frame.
Figure 3: Computational domain and CFD simulation result, (a) computational domain and boundary conditions, (b) analysis results of pitching angle 0°, (c) analysis results of pitching angle 30°, (d) forces and moments result obtained by the CFD simulation.
Figure 4: Software Architecture for the Entire System
Figure 5: Experimental pool in real and simulation environments.
Figure 6: Comparison of experimental and simulated motions in locomotion (a) swimming, (b) trot gait, (c) walk gait.
Figure 7: Comparision of locomotion velcity in experiments and simulations.
Figure 8: Crab walk ability of the optional and time variation of the position.
Figure 9: Comparison of joint angle data for the left front leg-fin, (a) swimming, (b) trot gait, (c) walk gait, (d) crab gait.
Figure 10: Multifunctional locomotion of two motion generation. (a) snapshot of the motion, (b) output signals of each joint, euler, and depth data.
Figure 11: Multifunctional locomotion of multimodal sensory feedback. (a) snapshot of the locomotion, (b) output signals of each joint.
Figure 12: Clustering Detection Results for Walls and Floors in water.