Résumé:
This thesis deals with the design, geometric, kinematic and dynamic modeling of bionic
flexible robots. In particular, we are mainly interested in cable-driven flexible robots and a
bionic robot named ‘‘Compact Bionic Handling Assistant (CBHA)’’.
Initially, we have proposed two kind of design of flexible robots, including a planar robot
and a space robot, both powered by cables. Based on this study, we have undertaken the
construction of a prototype with a single flexible section. This design and realization have
also been used to estimate the inertial parameters that will be used in the dynamic models of
these prototypes. First, we have developed the mathematical formulations describing the
structure of the flexible robots which represents a general case of multi-section flexible
robots. Next, we have developed an approach for solving the problem of inverse geometric
modeling of multi-section flexible robots, assuming that each flexible section bends as a
circular arc while keeping the principal axis of the structure inextensible. The problem was
formulated mathematically in terms of optimization of a quadratic cost function under some
constraints of equality (lengths conservation). The problem has been solved by developing an
optimization algorithm including metaheuristic methods, namely the Particle Swarm
Optimization (PSO) and the Genetic Algorithm (GA). This approach was validated by
simulation and two experimental test benches performed on the CBHA robot. Then, we have
also proposed dynamic models, direct and inverse, for the two cable-driven flexible robots,
planar and spatial, using the Lagrange method. In order to simplify the calculations and avoid
some numerical singularities, the dynamic models were approximated by expansion of
Taylor's series. These models have been validated by simulations under the MATLAB
environment. In addition, the inverse dynamic model was validated by real measurements
obtained from the robot UR5. Finally, a proportional-integral-derivative controller (PID) has
been proposed to track trajectories using the point-to-point method.
