Learning Humanoid Traversability

We explore discrete search-based contact space planning for humanoids using both palm and foot contact in complex unstructured environments. With a high branching factor and sparse contactable regions, it is challenging for the planner to find a contact sequence in such environments quickly. Therefore, we propose to learn a function which predicts traversability---a measure of how quickly the contact space planner can generate contact sequences to traverse a certain region. By including a learned traversability estimate into the heuristic function of the contact space planner, we can bias the planner to search the areas with more contactable regions, and thus find contact sequences more efficiently. In this paper we propose and evaluate two kinds of feature vectors for estimating traversability: Exact Contact Checking (ECC) and Approximate Contact Checking (ACC), which make different trade-offs between speed and accuracy. The experimental results show that the proposed approach using ACC outperforms both ECC and the baseline heuristic for contact space planning; ACC increases the planning success rate by 19% and reduces average planning time by 24% compared to the baseline in difficult environments with uneven terrain.

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Mobile Manipulator Motion Planning

We proposed an object search planner based on A* search algorithm with tree node sampling. The proposed approach combines visual and arm manipulation search. In other words, the robot searches occluded target object by either repositioning one of the accessible object with its arm or moving its platform to view the environment from a different pose. We evaluate the proposed approach with experiment performed by real robot in the scenario which objects may occlude or block access to one another.

In addition, we also proposed an algorithm for a mobile manipulator to reach target and avoid collision simultaneously. The algorithm utilizes potential fields to guide the local motion of the manipulator, detects possible cases when a local minimum is encountered, and escape local minimum with predefined strategies corresponding to each case.

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• Date: January 2017
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• Category: Website Design

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• Client: Window
• Category: Photography

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