Jul 26, 2018 · In this paper we combine these recent advances with techniques from sampling-based motion planning (SBMP) in order to design a methodology capable of planning for high-dimensional robotic systems beyond the reach of traditional approaches (e.g., humanoids, or even systems where planning occurs in the visual space).

In Chapters 2 and 3, on configuration space and rigid-body motions, we'll study the representation of positions, velocities, and forces in three-dimensional space. A firm understanding of this material is arguably the most important foundation for the further study of robotics, since all robots move in the physical world.

This paper introduces a motion planning method for capture of tumbling objects using a free-floating space robot. The proposed approach incorporates an improved Rapidly Exploring Random Tree Star (RRT*) algorithm enabling obstacle avoidance and generating desired trajectories for the robot’s end-effectors.

Mar 1, 2015 · In this paper, we survey some of our recent work on solving two important challenges related to configuration spaces: how to efficiently compute an approximate representation of high-dimensional configuration spaces; and how to efficiently perform geometric proximity and motion planning queries in high-dimensional configuration spaces.

Aug 16, 2021 · We introduce feedback motion primitives and heuristics to guide motion planning and demonstrate its use on a rover in 2D and a fixed-wing drone in 3D. Second, we introduce combined motion planning and hybrid feedback control design in order to find and follow trajectories under Metric Interval Temporal Logic (MITL) specifications.

Mar 13, 2024 · Inspired by the distributed control of octopuses' limbs, we develop a multi-level decentralized motion planning framework to manage the movement of different arms of space robots. This motion planning framework integrates naturally with the multi-agent reinforcement learning (MARL) paradigm.

Feb 27, 2019 · Abstract: This letter presents latent sampling-based motion planning (L-SBMP), a methodology toward computing motion plans for complex robotic systems by learning a plannable latent representation. Recent works in control of robotic systems have effectively leveraged local, low-dimensional embeddings of high-dimensional dynamics.

2 days ago · The ability to autonomously traverse and locomote across terrains of varying gradients and to overcome obstacles or extreme surfaces remains a capability firmly associated with animals ().Despite substantial advances in robotic locomotion and exploration, the versatility, efficiency, and autonomy of robots typically limit their application to a small range of preknown terrains or environmental ...

Feb 20, 2025 · Current self-reconfigurable modular robots and robotic collectives have demonstrated a variety of complex behaviors. Specifically, some show intricate shape changes but are not cohesive and do not support loads (8, 9).Others show emergent locomotion behaviors but do not directly control reconfiguration (10, 11).Yet others can support or even push loads but cannot reconfigure (12–15 ...

Feb 17, 2025 · In robot motion planning, APF constructs a potential energy function that consists of two components: an attractive potential field and a repulsive potential field. ... Feng, C. Fast-RRT*: An Improved Motion Planner for Mobile Robot in Two-Dimensional Space. IEEJ Trans. Electr. Electron. Eng. 2022, 17, 200–208. [Google Scholar] Karaman, S ...