diff --git a/test/base/test_batch.py b/test/base/test_batch.py
index e2390de..a9f2cdd 100644
--- a/test/base/test_batch.py
+++ b/test/base/test_batch.py
@@ -9,6 +9,10 @@ from tianshou.data import Batch, to_torch
 
 def test_batch():
     assert list(Batch()) == []
+    assert Batch().is_empty()
+    assert not Batch(a=[1, 2, 3]).is_empty()
+    with pytest.raises(AssertionError):
+        Batch({1: 2})
     batch = Batch(a=[torch.ones(3), torch.ones(3)])
     assert torch.allclose(batch.a, torch.ones(2, 3))
     batch = Batch(obs=[0], np=np.zeros([3, 4]))
diff --git a/tianshou/data/batch.py b/tianshou/data/batch.py
index e14b98f..6b10517 100644
--- a/tianshou/data/batch.py
+++ b/tianshou/data/batch.py
@@ -50,6 +50,12 @@ def _create_value(inst: Any, size: int) -> Union[
         return np.array([None for _ in range(size)])
 
 
+def _assert_type_keys(keys):
+    keys = list(keys)
+    assert all(isinstance(e, str) for e in keys), \
+        f"keys should all be string, but got {keys}"
+
+
 class Batch:
     """Tianshou provides :class:`~tianshou.data.Batch` as the internal data
     structure to pass any kind of data to other methods, for example, a
@@ -247,6 +253,7 @@ class Batch:
             batch_dict = deepcopy(batch_dict)
         if batch_dict is not None:
             if isinstance(batch_dict, (dict, Batch)):
+                _assert_type_keys(batch_dict.keys())
                 for k, v in batch_dict.items():
                     if isinstance(v, (list, tuple, np.ndarray)):
                         v_ = None
@@ -511,12 +518,14 @@ class Batch:
                 raise TypeError(s)
 
     @staticmethod
-    def cat(batches: List['Batch']) -> 'Batch':
-        """Concatenate a :class:`~tianshou.data.Batch` object into a single
+    def cat(batches: List[Union[dict, 'Batch']]) -> 'Batch':
+        """Concatenate a list of :class:`~tianshou.data.Batch` object into a single
         new batch.
         """
         batch = Batch()
         for batch_ in batches:
+            if isinstance(batch_, dict):
+                batch_ = Batch(batch_)
             batch.cat_(batch_)
         return batch
 
@@ -531,6 +540,7 @@ class Batch:
         keys_shared = set.intersection(*keys_map)
         values_shared = [
             [e[k] for e in batches] for k in keys_shared]
+        _assert_type_keys(keys_shared)
         for k, v in zip(keys_shared, values_shared):
             if all(isinstance(e, (dict, Batch)) for e in v):
                 self.__dict__[k] = Batch.stack(v, axis)
@@ -542,6 +552,7 @@ class Batch:
                     v = v.astype(np.object)
                 self.__dict__[k] = v
         keys_partial = reduce(set.symmetric_difference, keys_map)
+        _assert_type_keys(keys_partial)
         for k in keys_partial:
             for i, e in enumerate(batches):
                 val = e.get(k, None)
@@ -554,7 +565,7 @@ class Batch:
                         self.__dict__[k][i] = val
 
     @staticmethod
-    def stack(batches: List['Batch'], axis: int = 0) -> 'Batch':
+    def stack(batches: List[Union[dict, 'Batch']], axis: int = 0) -> 'Batch':
         """Stack a :class:`~tianshou.data.Batch` object into a single new
         batch.
         """
@@ -615,6 +626,9 @@ class Batch:
             raise TypeError("Object of type 'Batch' has no len()")
         return min(r)
 
+    def is_empty(self):
+        return len(self.__dict__.keys()) == 0
+
     @property
     def shape(self) -> List[int]:
         """Return self.shape."""