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I am also confused about this problem before.But we can look at test.py # use only last predicted pose in the following prediction last_pose = predict_pose_seq[-1]#[6] for i in range(len(last_pose)): last_pose[i] += answer[-1][i] # normalize angle to -Pi...Pi over y axis last_pose[0] = (last_pose[0] + np.pi) % (2 * np.pi) - np.pi answer.append(last_pose.tolist()) # print("answerlen",len(answer))
ground truth and the output of the model are consistent.So,it is right.
I saw you got the relative pose by minus operation, but shouldn't we got the relative pose by times operation of two absolute pose?
such as 2T1 = inv(wT2) dot (wT1)
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