Proceedings ArticleDOI
Combining planning techniques for manipulation using realtime perception
Ioan A. Sucan,Mrinal Kalakrishnan,Sachin Chitta +2 more
- pp 2895-2901
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TLDR
A novel combination of motion planning techniques to compute motion plans for robotic arms that move the arm as close as possible to the goal region using sampling-based planning and then switch to a trajectory optimization technique for the last few centimeters necessary to reach the goal area.Abstract:
We present a novel combination of motion planning techniques to compute motion plans for robotic arms. We compute plans that move the arm as close as possible to the goal region using sampling-based planning and then switch to a trajectory optimization technique for the last few centimeters necessary to reach the goal region. This combination allows fast computation and safe execution of motion plans even when the goals are very close to objects in the environment. The system incorporates realtime sensory inputs and correctly deals with occlusions that can occur when robot body parts block the sensor view of the environment. The system is tested on a 7 degree-of-freedom robot arm with sensory input from a tilting laser scanner that provides 3D information about the environment.read more
Citations
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Proceedings ArticleDOI
STOMP: Stochastic trajectory optimization for motion planning
TL;DR: It is experimentally show that the stochastic nature of STOMP allows it to overcome local minima that gradient-based methods like CHOMP can get stuck in.
Proceedings ArticleDOI
Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization
TL;DR: A novel approach for incorporating collision avoidance into trajectory optimization as a method of solving robotic motion planning problems, solving a suite of 7-degree-of-freedom arm-planning problems and 18-DOF full-body planning problems and benchmarked the algorithm against several other motion planning algorithms.
Book ChapterDOI
Towards Reliable Grasping and Manipulation in Household Environments
TL;DR: This work combines aspects such as scene interpretation from 3D range data, grasp planning, motion planning, and grasp failure identification and recovery using tactile sensors, aiming to address the uncertainty due to sensor and execution errors.
Proceedings ArticleDOI
Planning for autonomous door opening with a mobile manipulator
TL;DR: This paper shows how to overcome the high-dimensionality of the planning problem by identifying a graph-based representation that is small enough for efficient planning yet rich enough to contain feasible motions that open doors.
Journal ArticleDOI
Mobile Manipulation in Unstructured Environments: Perception, Planning, and Execution
TL;DR: This work presents an approach to mobile pick and place in human environments using a combination of two-dimensional and three-dimensional visual processing, tactile and proprioceptive sensor data, fast motion planning, reactive control and monitoring, and reactive grasping.
References
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MonographDOI
Planning Algorithms: Introductory Material
TL;DR: This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms, into planning under differential constraints that arise when automating the motions of virtually any mechanical system.
Journal Article
Rapidly-exploring random trees : a new tool for path planning
TL;DR: The Rapidly-exploring Random Tree (RRT) as discussed by the authors is a data structure designed for path planning problems with high degrees of freedom and non-holonomic constraints, including dynamics.
Book
Principles of Robot Motion: Theory, Algorithms, and Implementations
Howie Choset,Jean-Claude Latombe +1 more
TL;DR: In this paper, the mathematical underpinnings of robot motion are discussed and a text that makes the low-level details of implementation to high-level algorithmic concepts is presented.