Safe path planning is critical for bipedal robots to operate in safety-critical environments. Common path planning algorithms, such as RRT or RRT*, typically use geometric or kinematic collision check algorithms to ensure collision-free paths toward the target position. However, such approaches may generate non-smooth paths that do not comply with the dynamics constraints of walking robots. It has been shown that the control barrier function (CBF) can be integrated with RRT/RRT* to synthesize dynamically feasible collision-free paths. Yet, existing work has been limited to simple circular or elliptical shape obstacles due to the challenging nature of constructing appropriate barrier functions to represent irregularly shaped obstacles. In this paper, we present a CBF-based RRT* algorithm for bipedal robots to generate a collision-free path through space with multiple polynomial-shaped obstacles. In particular, we used logistic regression to construct polynomial barrier functions from a grid map of the environment to represent irregularly shaped obstacles. Moreover, we developed a multi-step CBF steering controller to ensure the efficiency of free space exploration. The proposed approach was first validated in simulation for a differential drive model, and then experimentally evaluated with a 3D humanoid robot, Digit, in a lab setting with randomly placed obstacles.
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This content will become publicly available on May 1, 2024
Spatio-temporal Motion Planning for Autonomous Vehicles with Trapezoidal Prism Corridors and Bézier Curves
Safety-guaranteed motion planning is critical for
self-driving cars to generate collision-free trajectories. A layered
motion planning approach with decoupled path and speed
planning is widely used for this purpose. This approach is
prone to be suboptimal in the presence of dynamic obstacles.
Spatial-temporal approaches deal with path planning and speed
planning simultaneously; however, the existing methods only
support simple-shaped corridors like cuboids, which restrict the
search space for optimization in complex scenarios. We propose
to use trapezoidal prism-shaped corridors for optimization,
which significantly enlarges the solution space compared to
the existing cuboidal corridors-based method. Finally, a piecewise Bezier curve optimization is conducted in our proposed ´
corridors. This formulation theoretically guarantees the safety
of the continuous-time trajectory. We validate the efficiency
and effectiveness of the proposed approach in numerical and
CommonRoad simulations
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- Award ID(s):
- 1950811
- NSF-PAR ID:
- 10442274
- Date Published:
- Journal Name:
- Proceedings of the American Control Conference
- ISSN:
- 0743-1619
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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